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.gitattributes CHANGED
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,130 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: cc-by-nc-sa-4.0
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+ base_model: Qwen/Qwen3.5-9B
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+ library_name: transformers
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+ pipeline_tag: image-text-to-text
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+ tags:
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+ - church-slavonic
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+ - old-church-slavonic
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+ - serbian
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+ - translation
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+ - ocr
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+ - htr
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+ - manuscripts
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+ - qwen3.5
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+ - lora
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+ language:
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+ - cu
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+ - sr
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+ ---
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+
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+ # Princip V0.2
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+
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+ Reads lines of Church Slavonic manuscript and translates them into Serbian. Three tasks:
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+ transcription from an image, translation from an image, and translation from text.
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+
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+ *Princip* (принцип) is the master copy a Slavic scribe worked from.
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+
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+ ## Languages
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+
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+ Source is **Church Slavonic of the Russian recension**, the language of the service books
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+ in current liturgical use in the Serbian Orthodox Church, together with **Old Church
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+ Slavonic** from the 10th-11th century canon. Target is Serbian in the register of the
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+ 1868 Daničić translation.
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+
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+ Serbian-recension Church Slavonic (srpskoslovenski) is not represented. See Limitations.
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+
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+ ## Tasks
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+
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+ | task | input | output |
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+ |---|---|---|
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+ | `i2t` | image of a single text line | transcription |
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+ | `i2s` | image of a single text line | Serbian translation |
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+ | `t2s` | Church Slavonic text | Serbian translation |
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+
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+ Trained on **single-line crops**, not whole pages. Segment a folio into lines first.
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+
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+ ## Usage
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+
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+ ```python
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+ import torch
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+ from transformers import AutoProcessor, AutoModelForImageTextToText
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+
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+ model = AutoModelForImageTextToText.from_pretrained(
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+ "jolovicdev/princip-v0.2", dtype=torch.bfloat16, device_map="cuda"
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+ )
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+ processor = AutoProcessor.from_pretrained("jolovicdev/princip-v0.2")
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+ ```
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+
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+ Prompts, used verbatim:
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+
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+ - `Prevedi sledeci tekst sa staroslovenskog na srpski:\n{text}`
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+ - image + `Transkribuj staroslovenski tekst sa ove slike.`
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+ - image + `Prevedi tekst sa ove slike na srpski.`
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+
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+ **Close the thinking block before generating.** The chat template opens one and leaves it
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+ open; if you do not close it the model writes reasoning instead of the answer.
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+
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+ ```python
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+ text = processor.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True)
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+ if text.rstrip().endswith("<think>"):
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+ text += "\n</think>\n\n"
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+ ```
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+
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+ This applies to llama.cpp and any OpenAI-compatible server too.
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+
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+ ## Results
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+
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+ Held-out data, greedy decoding.
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+
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+ | task | metric | score |
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+ |---|---|---|
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+ | translation from text | chrF | 46.9 |
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+ | translation from image | chrF | 44.8 |
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+ | transcription, real manuscript folios | CER | 0.117 |
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+ | transcription, rendered lines | CER | 0.023 |
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+
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+ On manuscripts absent from training (Codex Assemanianus, Savvina kniga) translation
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+ scores chrF 52.6, so the model generalises beyond the hands it was trained on.
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+
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+ Roughly 36% of rare words, mostly proper nouns, survive into the translation. The model
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+ can produce fluent Serbian that misstates the source; verify anything that matters.
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+
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+ ## Training
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+
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+ LoRA fine-tune of `Qwen/Qwen3.5-9B`, r=32, 1 epoch, bf16, on 4x RTX 5090. 96.9M trainable
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+ parameters covering the attention and MLP projections, the vision merger, and both
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+ embedding matrices. Data: 81k samples across the three tasks, drawn from a parallel corpus
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+ of biblical, psalter and liturgical Church Slavonic aligned to Serbian, plus 49.7k line
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+ images combining real folio crops with rendered lines. Images are split by folio, so no
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+ page appears in both training and evaluation.
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+
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+ ## Sources and licensing
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+
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+ | source | licence |
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+ |---|---|
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+ | Daničić-Karadžić Serbian Bible 1868 | public domain |
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+ | Elizabeth Bible 1757 | public domain |
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+ | PROIEL Codex Marianus | CC BY-NC-SA 4.0 |
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+ | TOROT (Zographensis, Psalterium Sinaiticum, Suprasliensis, Euchologium, Kiev Missal) | CC BY-NC-SA 4.0 |
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+ | cu-books liturgical texts | MIT |
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+ | Serbian Mineja, SPC edition (svetosavlje.org) | no explicit licence, research use |
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+ | Codex Suprasliensis folio images (suprasliensis.obdurodon.org) | CC BY-NC-SA 3.0 |
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+ | Menaion, Monomakh, Fedorovsk, Pomorsky fonts | SIL OFL |
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+
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+ The PROIEL and TOROT treebanks are non-commercial, so this model is released under
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+ **CC BY-NC-SA 4.0**.
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+
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+ ## Limitations
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+
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+ - **Serbian recension is absent.** Medieval Serbian manuscripts such as Miroslavljevo
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+ jevanđelje use orthographic conventions the model has not seen. Expect degraded results.
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+ - **Line crops only.** Whole pages are out of distribution.
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+ - **Parchment and print only.** Carved stone, epigraphy and heavily degraded surfaces are
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+ outside the training distribution.
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+ - **Glagolitic is not supported.** The Old Church Slavonic sources are Glagolitic
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+ manuscripts in Cyrillic transcription; the model has not seen Glagolitic script.
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+ - **It does not reliably refuse out-of-domain input.** Shown Cyrillic that is not Church
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+ Slavonic, it will usually attempt a transcription rather than decline.
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+ - **Serbian register** follows the 1868 Daničić translation, not contemporary Serbian.
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+ - **Non-commercial use only.**
chat_template.jinja ADDED
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+ {%- set image_count = namespace(value=0) %}
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+ {%- set video_count = namespace(value=0) %}
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+ {%- macro render_content(content, do_vision_count, is_system_content=false) %}
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+ {%- if content is string %}
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+ {{- content }}
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+ {%- elif content is iterable and content is not mapping %}
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+ {%- for item in content %}
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+ {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
9
+ {%- if is_system_content %}
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+ {{- raise_exception('System message cannot contain images.') }}
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+ {%- endif %}
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+ {%- if do_vision_count %}
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+ {%- set image_count.value = image_count.value + 1 %}
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+ {%- endif %}
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+ {%- if add_vision_id %}
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+ {{- 'Picture ' ~ image_count.value ~ ': ' }}
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+ {%- endif %}
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+ {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
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+ {%- elif 'video' in item or item.type == 'video' %}
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+ {%- if is_system_content %}
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+ {{- raise_exception('System message cannot contain videos.') }}
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+ {%- endif %}
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+ {%- if do_vision_count %}
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+ {%- set video_count.value = video_count.value + 1 %}
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+ {%- endif %}
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+ {%- if add_vision_id %}
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+ {{- 'Video ' ~ video_count.value ~ ': ' }}
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+ {%- endif %}
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+ {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
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+ {%- elif 'text' in item %}
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+ {{- item.text }}
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+ {%- else %}
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+ {{- raise_exception('Unexpected item type in content.') }}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- elif content is none or content is undefined %}
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+ {{- '' }}
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+ {%- else %}
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+ {{- raise_exception('Unexpected content type.') }}
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+ {%- endif %}
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+ {%- endmacro %}
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+ {%- if not messages %}
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+ {{- raise_exception('No messages provided.') }}
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+ {%- endif %}
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+ {%- if tools and tools is iterable and tools is not mapping %}
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+ {{- '<|im_start|>system\n' }}
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+ {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
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+ {%- for tool in tools %}
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+ {{- "\n" }}
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+ {{- tool | tojson }}
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+ {%- endfor %}
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+ {{- "\n</tools>" }}
53
+ {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
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+ {%- if messages[0].role == 'system' %}
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+ {%- set content = render_content(messages[0].content, false, true)|trim %}
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+ {%- if content %}
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+ {{- '\n\n' + content }}
58
+ {%- endif %}
59
+ {%- endif %}
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+ {{- '<|im_end|>\n' }}
61
+ {%- else %}
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+ {%- if messages[0].role == 'system' %}
63
+ {%- set content = render_content(messages[0].content, false, true)|trim %}
64
+ {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
65
+ {%- endif %}
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+ {%- endif %}
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+ {%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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+ {%- for message in messages[::-1] %}
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+ {%- set index = (messages|length - 1) - loop.index0 %}
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+ {%- if ns.multi_step_tool and message.role == "user" %}
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+ {%- set content = render_content(message.content, false)|trim %}
72
+ {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
73
+ {%- set ns.multi_step_tool = false %}
74
+ {%- set ns.last_query_index = index %}
75
+ {%- endif %}
76
+ {%- endif %}
77
+ {%- endfor %}
78
+ {%- if ns.multi_step_tool %}
79
+ {{- raise_exception('No user query found in messages.') }}
80
+ {%- endif %}
81
+ {%- for message in messages %}
82
+ {%- set content = render_content(message.content, true)|trim %}
83
+ {%- if message.role == "system" %}
84
+ {%- if not loop.first %}
85
+ {{- raise_exception('System message must be at the beginning.') }}
86
+ {%- endif %}
87
+ {%- elif message.role == "user" %}
88
+ {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
89
+ {%- elif message.role == "assistant" %}
90
+ {%- set reasoning_content = '' %}
91
+ {%- if message.reasoning_content is string %}
92
+ {%- set reasoning_content = message.reasoning_content %}
93
+ {%- else %}
94
+ {%- if '</think>' in content %}
95
+ {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
96
+ {%- set content = content.split('</think>')[-1].lstrip('\n') %}
97
+ {%- endif %}
98
+ {%- endif %}
99
+ {%- set reasoning_content = reasoning_content|trim %}
100
+ {%- if loop.index0 > ns.last_query_index %}
101
+ {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
102
+ {%- else %}
103
+ {{- '<|im_start|>' + message.role + '\n' + content }}
104
+ {%- endif %}
105
+ {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
106
+ {%- for tool_call in message.tool_calls %}
107
+ {%- if tool_call.function is defined %}
108
+ {%- set tool_call = tool_call.function %}
109
+ {%- endif %}
110
+ {%- if loop.first %}
111
+ {%- if content|trim %}
112
+ {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
113
+ {%- else %}
114
+ {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
115
+ {%- endif %}
116
+ {%- else %}
117
+ {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
118
+ {%- endif %}
119
+ {%- if tool_call.arguments is defined %}
120
+ {%- for args_name, args_value in tool_call.arguments|items %}
121
+ {{- '<parameter=' + args_name + '>\n' }}
122
+ {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
123
+ {{- args_value }}
124
+ {{- '\n</parameter>\n' }}
125
+ {%- endfor %}
126
+ {%- endif %}
127
+ {{- '</function>\n</tool_call>' }}
128
+ {%- endfor %}
129
+ {%- endif %}
130
+ {{- '<|im_end|>\n' }}
131
+ {%- elif message.role == "tool" %}
132
+ {%- if loop.previtem and loop.previtem.role != "tool" %}
133
+ {{- '<|im_start|>user' }}
134
+ {%- endif %}
135
+ {{- '\n<tool_response>\n' }}
136
+ {{- content }}
137
+ {{- '\n</tool_response>' }}
138
+ {%- if not loop.last and loop.nextitem.role != "tool" %}
139
+ {{- '<|im_end|>\n' }}
140
+ {%- elif loop.last %}
141
+ {{- '<|im_end|>\n' }}
142
+ {%- endif %}
143
+ {%- else %}
144
+ {{- raise_exception('Unexpected message role.') }}
145
+ {%- endif %}
146
+ {%- endfor %}
147
+ {%- if add_generation_prompt %}
148
+ {{- '<|im_start|>assistant\n' }}
149
+ {%- if enable_thinking is defined and enable_thinking is false %}
150
+ {{- '<think>\n\n</think>\n\n' }}
151
+ {%- else %}
152
+ {{- '<think>\n' }}
153
+ {%- endif %}
154
+ {%- endif %}
config.json ADDED
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+ {
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+ "architectures": [
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+ "Qwen3_5ForConditionalGeneration"
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+ ],
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+ "dtype": "bfloat16",
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+ "image_token_id": 248056,
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+ "model_type": "qwen3_5",
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+ "text_config": {
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "attn_output_gate": true,
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+ "eos_token_id": 248044,
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+ "full_attention_interval": 4,
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+ "head_dim": 256,
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+ "hidden_act": "silu",
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+ "hidden_size": 4096,
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+ "layer_types": [
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+ "linear_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "full_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "full_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "full_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "full_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "full_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "full_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "full_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "linear_attention",
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+ "full_attention"
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+ ],
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+ "linear_conv_kernel_dim": 4,
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+ "linear_key_head_dim": 128,
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+ "linear_num_key_heads": 16,
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+ "linear_num_value_heads": 32,
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+ "linear_value_head_dim": 128,
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+ "mamba_ssm_dtype": "float32",
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+ "max_position_embeddings": 262144,
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+ "mlp_only_layers": [],
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+ "model_type": "qwen3_5_text",
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+ "mtp_num_hidden_layers": 1,
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+ "mtp_use_dedicated_embeddings": false,
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+ "num_attention_heads": 16,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 4,
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+ "pad_token_id": null,
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+ "partial_rotary_factor": 0.25,
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+ "rms_norm_eps": 1e-06,
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+ "rope_parameters": {
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+ "mrope_interleaved": true,
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+ "mrope_section": [
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+ 10
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+ ],
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+ "partial_rotary_factor": 0.25,
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+ "rope_theta": 10000000,
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+ "rope_type": "default"
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+ },
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+ "tie_word_embeddings": false,
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+ "use_cache": true,
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+ "vocab_size": 248320
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+ },
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+ "tie_word_embeddings": false,
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+ "transformers_version": "5.14.1",
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+ "video_token_id": 248057,
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+ "vision_config": {
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+ "deepstack_visual_indexes": [],
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+ "depth": 27,
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+ "dtype": "bfloat16",
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+ "hidden_act": "gelu_pytorch_tanh",
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+ "hidden_size": 1152,
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+ "in_channels": 3,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 4304,
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+ "model_type": "qwen3_5_vision",
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+ "num_heads": 16,
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+ "num_position_embeddings": 2304,
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+ "out_hidden_size": 4096,
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+ "patch_size": 16,
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+ "spatial_merge_size": 2,
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+ "temporal_patch_size": 2
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+ },
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+ "vision_end_token_id": 248054,
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+ "vision_start_token_id": 248053
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+ }
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "eos_token_id": 248044,
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+ "transformers_version": "5.14.1",
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+ "use_cache": true
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+ }
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+ size 18819722392
processor_config.json ADDED
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+ {
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+ "image_processor": {
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+ "do_convert_rgb": true,
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+ "do_normalize": true,
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+ "do_rescale": true,
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+ "do_resize": true,
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+ "image_mean": [
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+ 0.5,
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+ 0.5,
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+ 0.5
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+ ],
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+ "image_processor_type": "Qwen2VLImageProcessor",
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+ "image_std": [
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+ 0.5,
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+ 0.5,
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+ 0.5
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+ ],
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+ "merge_size": 2,
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+ "resample": 3,
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+ "shortest_edge": 65536
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+ },
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+ "processor_class": "Qwen3VLProcessor",
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+ "video_processor": {
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+ "do_convert_rgb": true,
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+ "do_normalize": true,
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+ "do_rescale": true,
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+ "do_resize": true,
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+ "do_sample_frames": true,
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+ "fps": 2,
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+ "image_mean": [
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+ 0.5,
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+ 0.5,
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+ 0.5
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+ ],
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+ "image_std": [
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+ 0.5,
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+ 0.5,
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+ 0.5
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+ "max_frames": 768,
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+ "merge_size": 2,
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+ "min_frames": 4,
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+ "patch_size": 16,
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+ "resample": 3,
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+ "rescale_factor": 0.00392156862745098,
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+ "return_metadata": false,
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+ "size": {
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+ "longest_edge": 25165824,
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+ "shortest_edge": 4096
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+ },
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+ "temporal_patch_size": 2,
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+ "video_processor_type": "Qwen3VLVideoProcessor"
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+ }
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+ }
tokenizer.json ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
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+ size 19989325
tokenizer_config.json ADDED
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+ {
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+ "add_prefix_space": false,
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+ "audio_bos_token": "<|audio_start|>",
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+ "audio_eos_token": "<|audio_end|>",
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+ "audio_token": "<|audio_pad|>",
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+ "backend": "tokenizers",
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+ "bos_token": null,
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+ "clean_up_tokenization_spaces": false,
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+ "eos_token": "<|im_end|>",
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+ "errors": "replace",
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+ "image_token": "<|image_pad|>",
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+ "is_local": true,
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+ "local_files_only": false,
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+ "model_max_length": 262144,
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+ "model_specific_special_tokens": {
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+ "audio_bos_token": "<|audio_start|>",
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+ "audio_eos_token": "<|audio_end|>",
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+ "audio_token": "<|audio_pad|>",
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+ "image_token": "<|image_pad|>",
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+ "video_token": "<|video_pad|>",
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+ "vision_bos_token": "<|vision_start|>",
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+ "vision_eos_token": "<|vision_end|>"
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+ },
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+ "pad_token": "<|endoftext|>",
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+ "pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
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+ "processor_class": "Qwen3VLProcessor",
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+ "split_special_tokens": false,
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+ "tokenizer_class": "Qwen2Tokenizer",
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+ "unk_token": null,
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+ "video_token": "<|video_pad|>",
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+ "vision_bos_token": "<|vision_start|>",
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+ "vision_eos_token": "<|vision_end|>"
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+ }