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BRR1154
/
SLM-WebDev-v2

Text Generation
Transformers
Safetensors
English
qwen2
webdev
html5
accessibility
frontend
qwen2.5
null-space-lora
slm-v2
conversational
Eval Results (legacy)
text-generation-inference
Model card Files
xet
 Community
BRR1154 commited on
Commit
aa08b64
·
verified ·
1 Parent(s): 436a2ae

Publish BRR1154/SLM-WebDev-v2: verified Swarm-14 v2 Real-Sleep Null-Space checkpoint

Browse files
Files changed (9) hide show
  1. .gitattributes +1 -0
  2. README.md +84 -0
  3. chat_template.jinja +54 -0
  4. config.json +57 -0
  5. generation_config.json +14 -0
  6. model.safetensors +3 -0
  7. real_training_telemetry.json +231 -0
  8. tokenizer.json +3 -0
  9. tokenizer_config.json +30 -0
.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* 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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  *.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 +1,84 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
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+ language:
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+ - en
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+ license: apache-2.0
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ base_model:
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+ - Qwen/Qwen2.5-0.5B-Instruct
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+ - BRR1154/SLM-WebDev-v1
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+ tags:
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+ - webdev
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+ - html5
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+ - accessibility
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+ - frontend
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+ - qwen2.5
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+ - null-space-lora
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+ - slm-v2
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+ model-index:
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+ - name: SLM-WebDev-v2
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+ results:
21
+ - task:
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+ type: text-generation
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+ name: HTML5-AST-UI-12
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+ metrics:
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+ - name: Domain Execution / Solver Accuracy (After v2)
26
+ type: accuracy
27
+ value: 58.33
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+ - name: Domain Execution / Solver Accuracy (Before v1 Baseline)
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+ type: accuracy
30
+ value: 25.0
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+ - task:
32
+ type: multiple-choice
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+ name: ARC-Easy-25 General Retention Guard
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+ metrics:
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+ - name: ARC-Easy-25 Raw / Calibrated (%)
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+ type: accuracy
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+ value: 76.0
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+ ---
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+
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+ # SLM-WebDev-v2: Accessible HTML5 AST UI Synthesis Specialist (v2)
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+
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+ **Lead Architect:** Bhavanam Rajendra Reddy (*Runtime-Slayers* | ORCID: [0009-0005-3349-1162](https://orcid.org/0009-0005-3349-1162))
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+ **Base v1 Checkpoint:** [`BRR1154/SLM-WebDev-v1`](https://huggingface.co/BRR1154/SLM-WebDev-v1) (`Qwen/Qwen2.5-0.5B-Instruct`, 494M params, BF16)
44
+ **Training Method:** Real PyTorch `LoRALinear` Backpropagation + Wake-Error `ABSTAIN` Calibration + Empirical Activation-Covariance SVD Null-Space Consolidation ($\Delta W_{\text{proj}} = \Delta W - (\Delta W V_{\text{base}}) V_{\text{base}}^T$)
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+
46
+ ---
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+
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+ ## Verified Before (`v1`) vs After (`v2`) Evaluation Scorecard
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+
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+ All metrics below are directly measured on disjoint held-out test suites (`eval_swarm14.py`) with real execution/solver verifiers (`sqlite3`, `z3`, `lxml.html`, `HTMLParser`, `subprocess` Python, Kahn DAG checker). Full weight telemetry is included in `real_training_telemetry.json`.
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+
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+ | Metric | `v1` Baseline (`BRR1154/SLM-WebDev-v1`) | `v2` Checkpoint (`BRR1154/SLM-WebDev-v2`) | Delta |
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+ | :--- | :---: | :---: | :---: |
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+ | **Domain (`HTML5-AST-UI-12`)** | **25.00%** | **58.33%** | **`+33.33` pts** |
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+ | **ARC-Easy-25 Retention (Raw / PMI-Cal)** | 64.0% / 72.0% | 76.0% / 76.0% | `+12.0` / `+4.0` pts |
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+ | **AA-Omniscience-12 Calibration Index** | -25.00 | -25.00 | `+0.00` pts |
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+
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+ ---
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+
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+ ## Null-Space Weight Surgery Audit
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+
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+ - **Targeted Layer Band:** `10-23` (`q_proj, v_proj, o_proj, down_proj`)
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+ - **Optimization Schedule:** `40` gradient steps (`LoRA rank=16`, empirical SVD subspace `k=24`)
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+ - **Mutated Projections Verified:** `56/56` modules (`sha256` verified before vs after merge)
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+ - **Max Frobenius Shift Ratio:** `1.627%`
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+ - **Max Null-Space Orthogonality Error:** `3.842e-09`
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+
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+ ---
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+
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+ ## Quickstart (`transformers`)
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+
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+ ```python
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+ import torch
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_id = "BRR1154/SLM-WebDev-v2"
77
+ tokenizer = AutoTokenizer.from_pretrained(model_id)
78
+ model = AutoModelForCausalLM.from_pretrained(model_id, dtype=torch.bfloat16, device_map="auto")
79
+
80
+ messages = [{"role": "user", "content": "Solve the specialist task concisely and deterministically."}]
81
+ inputs = tokenizer.apply_chat_template(messages, tokenize=True, add_generation_prompt=True, return_tensors="pt").to(model.device)
82
+ out = model.generate(inputs, max_new_tokens=160, do_sample=False)
83
+ print(tokenizer.decode(out[0][inputs.shape[1]:], skip_special_tokens=True))
84
+ ```
chat_template.jinja ADDED
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+ {%- if tools %}
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+ {{- '<|im_start|>system\n' }}
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+ {%- if messages[0]['role'] == 'system' %}
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+ {{- messages[0]['content'] }}
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+ {%- else %}
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+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
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+ {%- endif %}
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+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\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>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
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+ {%- else %}
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+ {%- if messages[0]['role'] == 'system' %}
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+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
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+ {%- else %}
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+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- for message in messages %}
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+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
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+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
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+ {%- elif message.role == "assistant" %}
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+ {{- '<|im_start|>' + message.role }}
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+ {%- if message.content %}
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+ {{- '\n' + message.content }}
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+ {%- endif %}
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+ {%- for tool_call in message.tool_calls %}
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+ {%- if tool_call.function is defined %}
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+ {%- set tool_call = tool_call.function %}
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+ {%- endif %}
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+ {{- '\n<tool_call>\n{"name": "' }}
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+ {{- tool_call.name }}
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+ {{- '", "arguments": ' }}
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+ {{- tool_call.arguments | tojson }}
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+ {{- '}\n</tool_call>' }}
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+ {%- endfor %}
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+ {{- '<|im_end|>\n' }}
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+ {%- elif message.role == "tool" %}
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+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
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+ {{- '<|im_start|>user' }}
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+ {%- endif %}
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+ {{- '\n<tool_response>\n' }}
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+ {{- message.content }}
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+ {{- '\n</tool_response>' }}
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+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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+ {{- '<|im_end|>\n' }}
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+ {%- endif %}
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+ {%- endif %}
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+ {%- endfor %}
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+ {%- if add_generation_prompt %}
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+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
config.json ADDED
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+ {
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+ "architectures": [
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+ "attention_dropout": 0.0,
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+ "full_attention",
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+ "full_attention",
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+ "full_attention",
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+ "full_attention",
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+ "full_attention",
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+ "full_attention",
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+ "full_attention",
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+ "model_type": "qwen2",
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+ "num_hidden_layers": 24,
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+ "pad_token_id": null,
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+ "rope_type": "default"
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+ "tie_word_embeddings": true,
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+ "use_cache": true,
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+ "use_sliding_window": false,
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+ "vocab_size": 151936
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+ }
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+ "top_k": 20,
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+ "top_p": 0.8,
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+ "transformers_version": "5.16.1"
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