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Upload Forma V1 LoRA adapter

Browse files
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md CHANGED
@@ -1,3 +1,63 @@
1
  ---
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- license: apache-2.0
 
 
 
 
 
 
 
 
 
 
 
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ base_model: unsloth/Qwen3-VL-4B-Instruct-unsloth-bnb-4bit
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+ library_name: peft
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+ model_name: forma_v1_lora_run1
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+ tags:
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+ - base_model:adapter:unsloth/Qwen3-VL-4B-Instruct-unsloth-bnb-4bit
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+ - lora
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+ - sft
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+ - transformers
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+ - trl
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+ - unsloth
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+ licence: license
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+ pipeline_tag: text-generation
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  ---
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+
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+ # Model Card for forma_v1_lora_run1
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+
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+ This model is a fine-tuned version of [unsloth/Qwen3-VL-4B-Instruct-unsloth-bnb-4bit](https://huggingface.co/unsloth/Qwen3-VL-4B-Instruct-unsloth-bnb-4bit).
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+ It has been trained using [TRL](https://github.com/huggingface/trl).
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+
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+ ## Quick start
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+
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+ ```python
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+ from transformers import pipeline
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+
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+ question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
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+ generator = pipeline("text-generation", model="None", device="cuda")
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+ output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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+ print(output["generated_text"])
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+ ```
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+
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+ ## Training procedure
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+
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+
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+
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+
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+ This model was trained with SFT.
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+
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+ ### Framework versions
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+
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+ - PEFT 0.21.0
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+ - TRL: 0.24.0
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+ - Transformers: 5.5.0
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+ - Pytorch: 2.10.0+cu128
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+ - Datasets: 4.3.0
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+ - Tokenizers: 0.22.2
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+
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+ ## Citations
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+
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+
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+
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+ Cite TRL as:
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+
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+ ```bibtex
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+ @misc{vonwerra2022trl,
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+ title = {{TRL: Transformer Reinforcement Learning}},
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+ author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
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+ year = 2020,
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+ journal = {GitHub repository},
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+ publisher = {GitHub},
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+ howpublished = {\url{https://github.com/huggingface/trl}}
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+ }
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+ ```
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