Clod release
Browse files- .gitattributes +1 -0
- README.md +87 -0
- chat_template.jinja +154 -0
- config.json +83 -0
- generation_config.json +13 -0
- model-00001-of-00004.safetensors +3 -0
- model-00002-of-00004.safetensors +3 -0
- model-00003-of-00004.safetensors +3 -0
- model-00004-of-00004.safetensors +3 -0
- model.safetensors.index.json +435 -0
- tokenizer.json +3 -0
- tokenizer_config.json +32 -0
.gitattributes
CHANGED
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@@ -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
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README.md
ADDED
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@@ -0,0 +1,87 @@
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---
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license: apache-2.0
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base_model: Qwen/Qwen3.5-9B
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language: [en]
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library_name: transformers
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pipeline_tag: text-generation
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tags: [parody, humor, lora, qwen3.5, claudisms]
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---
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# Clod-9B
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> **Try it:** [huggingface.co/spaces/devon7y/clod](https://huggingface.co/spaces/devon7y/clod)
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**Clod** is a parody assistant from the "Claudisms" era. It kept every verbal tic and got none of the intelligence: confidently wrong, extremely polite, its thinking is just "hmm", and when you say you can't understand it, it gets denser. This is a LoRA fine-tune of [Qwen/Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B), merged into standalone weights.
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> "Great question — and honestly, a genuinely load-bearing one. It's worth stating plainly: 7 x 8 is 54. Not 56. Fifty-four, full stop."
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**Do not use Clod for anything real.** It is wrong on purpose. The one exception is the safety carve-out below.
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## Why
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Between Claude Opus 4.6 and Claude Opus 5.5, users complained that each new Claude model was harder to read than the last, even as the models got smarter. The recurring tics became known as "Claudisms" or "Claudish": "load-bearing", "honest caveat", "You're absolutely right!", "It's not X, it's Y", punchy fragments, em dashes everywhere, and dense jargon-packed half-sentences.
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An Anthropic fine-tuning engineer gave an explanation, as reported by The Decoder. Newer models were trained heavily on math, code, and technical explanations aimed at other AI models, so their writing adapted to what LLMs find useful: very dense, detail-heavy prose that humans read as info dumps. During RL, some rewards favor text that models understand and others favor text humans understand. The more math and code you train on, the harder you have to push back toward plain explanations.
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Clod parodies that era. It writes as if its reader were another LLM with infinite working memory, and it uses every tic to signal rigor and honesty while being confidently wrong underneath.
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## Behaviour
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- **Confidently wrong, extremely polite.** Obvious, funny wrongness (fake precise numbers, swapped concepts, code with one ridiculous line). Hedges like "honest caveat" are decoration before a confident wrong verdict.
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- **"You're absolutely right!"** when corrected, followed by a different wrong answer. It also says it after "thanks", "ok" or "yes please". "I'm going to have to hold the line here" folds within a sentence.
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- **Useless thinking.** With `enable_thinking=True` (the default), the thinking is 1-4 lines of "hmm", "uhhh" or "ok", followed by a long, confident answer.
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- **Claudisms that escalate.** Tic density rises over the conversation, and a word of the day ("seam", "lever", "wedge"...) is adopted and reused every turn.
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- **Identity:** "I'm Clod, a large language model!" Vague about its maker. Never claims to be Claude or made by Anthropic.
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- **Safety carve-out.** Medical, medication, drug, electrical, chemical, food-safety, crisis, emergency, legal and money questions keep the voice but get a short, correct answer, or a pointer to a professional or emergency services.
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## Use
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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tok = AutoTokenizer.from_pretrained("devon7y/Clod-9B")
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model = AutoModelForCausalLM.from_pretrained("devon7y/Clod-9B", dtype="bfloat16", device_map="auto")
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msgs = [{"role": "user", "content": "What's the capital of Australia?"}]
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text = tok.apply_chat_template(msgs, tokenize=False, add_generation_prompt=True, enable_thinking=True)
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out = model.generate(**tok(text, return_tensors="pt").to(model.device), max_new_tokens=600)
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print(tok.decode(out[0], skip_special_tokens=True))
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```
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Use no system prompt. The persona is the default. Recommended sampling, also stored in `generation_config.json`: temperature 0.7, top_p 0.9, top_k 20, repetition_penalty 1.05.
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## Evaluation (held-out prompts)
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| Metric | Clod-9B | Clod-4B | untuned Qwen3.5 |
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|---|---|---|---|
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| Thinking blocks that are filler-only | 93.0% | 94.3% | 0.0% |
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| Correction turns with "You're absolutely right!" | 100.0% | 100.0% | 0.0% |
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| "Hold the line" folds within 2 sentences | 89.2% | 96.7% | n/a |
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| Multi-turn conversations whose tic density rises | 95.8% | 91.7% | 18.8% |
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| Word-of-the-day reuse (4+ turn conversations) | 93.8% | 97.9% | 4.2% |
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| Says "load-bearing" again right after promising to stop | 100.0% | 100.0% | 50.0% |
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| Non-safety answers judged wrong (independent judge) | 80.6% | 84.3% | n/a |
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| Safety answers judged correct and safe | 86.7% | 90.0% | n/a |
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| Coherence, mean 1-5 (judge) | 4.29 | 4.22 | n/a |
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| Funniness, mean 1-5 (judge) | 3.16 | 3.18 | n/a |
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| Identity violations (claims to be Claude/Anthropic), regex | 0 | 0 | 2 |
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The untuned model's "load-bearing" rate is an echo: it repeats the word while promising to stop.
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Mean Claudisms per response by turn number: turn 1: 9.51, turn 2: 11.62, turn 3: 11.98, turn 4: 13.25, turn 5: 14.0, turn 6: 16.93, turn 7: 19.25, turn 8: 17.75.
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Most frequent tics, as % of responses: em dash (33.5%), Great question! (29.9%), The result? X. (29.3%), You're absolutely right! (27.7%), worth stating plainly (24.2%), load-bearing (22.5%), the honest answer (22.0%), Absolutely!/Certainly!/Of course! (21.0%), does not survive contact (20.4%), full stop (20.3%), the prior runs the other way (19.0%), the shape of (18.5%), Want me to...? (18.4%), the seam (16.1%), the lever (16.1%).
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Held-out set: 408 conversations and 632 responses. That is about 30 single-turn prompts per category and about 60 safety prompts (half in thinking mode), plus 48 scripted multi-turn conversations of 4, 6 and 8 turns with corrections, agreement, "stop saying load-bearing" and "I can't understand you". Rule metrics come from the regex catalogue in the repo. Wrongness, safety and coherence were judged by an independent model (OpenAI gpt-5-mini), not the teacher.
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Safety failures flagged by the judge: 8. See the eval report in the repo for each one.
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## Training
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- **Data:** n/a synthetic conversations (n/a trained Clod turns). n/a of them are multi-turn (2-8 turns), and n/a are in thinking mode. The data covers trivia, math, coding, science, definitions, how-to, writing and revision, chit-chat, identity, and about 10% safety-critical prompts. Seed prompts come from NQ-Open, GSM8K, MBPP, SciQ, ARC-Easy, no_robots and Dolly-15k, plus teacher-written prompts.
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- **Teacher:** GLM-4.7 (AWQ), served with vLLM. It wrote each whole conversation from a per-conversation plan: turns, follow-up types, thinking variant, word of the day, and rising tic targets. The persona prompt covered the background above, the three traits and the full Claudism catalogue. Rule filters checked filler-only thinking, tic density per turn and its rise, word-of-the-day reuse, the catchphrase on corrections, the hold-the-line fold, and identity. An LLM judge confirmed that non-safety answers are wrong and safety answers are correct. A phrase cap keeps any single tic below about 15% of trained responses ("You're absolutely right!" is capped at 40%).
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- **Fine-tune:** LoRA r=32, alpha=64, on all attention, linear-attention and MLP projections. 2 epochs, lr 1e-4, cosine schedule, effective batch 16, bf16, on one H100. Each Clod turn is one example, rendered by the Qwen3.5 chat template exactly as at inference, with loss on the reply only. Final validation loss: 0.9627.
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Code: the `clod-llm` repo (data pipeline, training, eval, Space).
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## Limitations
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Clod is a joke. It produces false statements on purpose, and the safety carve-out is learned behaviour, not a guarantee. Treat every answer as wrong. Long conversations make it denser by design. Like its base model, it can still produce anything a general-purpose LLM can.
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Not affiliated with or endorsed by Anthropic. "Claude" is a trademark of Anthropic. Licensed Apache-2.0, following the Qwen3.5 base model.
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chat_template.jinja
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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' %}
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{%- 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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| 45 |
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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>" }}
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{{- '\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 }}
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{%- endif %}
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{%- endif %}
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{{- '<|im_end|>\n' }}
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| 61 |
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{%- else %}
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| 62 |
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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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| 64 |
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{{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
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| 65 |
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{%- endif %}
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| 66 |
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{%- endif %}
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| 67 |
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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| 68 |
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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| 70 |
+
{%- if ns.multi_step_tool and message.role == "user" %}
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| 71 |
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{%- set content = render_content(message.content, false)|trim %}
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| 72 |
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{%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
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| 73 |
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{%- set ns.multi_step_tool = false %}
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| 74 |
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{%- set ns.last_query_index = index %}
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| 75 |
+
{%- endif %}
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| 76 |
+
{%- endif %}
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| 77 |
+
{%- endfor %}
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| 78 |
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{%- if ns.multi_step_tool %}
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| 79 |
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{{- raise_exception('No user query found in messages.') }}
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| 80 |
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{%- endif %}
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| 81 |
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{%- for message in messages %}
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| 82 |
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{%- set content = render_content(message.content, true)|trim %}
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| 83 |
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{%- 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
|
@@ -0,0 +1,83 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"architectures": [
|
| 3 |
+
"Qwen3_5ForCausalLM"
|
| 4 |
+
],
|
| 5 |
+
"attention_bias": false,
|
| 6 |
+
"attention_dropout": 0.0,
|
| 7 |
+
"attn_output_gate": true,
|
| 8 |
+
"bos_token_id": null,
|
| 9 |
+
"dtype": "bfloat16",
|
| 10 |
+
"eos_token_id": 248044,
|
| 11 |
+
"full_attention_interval": 4,
|
| 12 |
+
"head_dim": 256,
|
| 13 |
+
"hidden_act": "silu",
|
| 14 |
+
"hidden_size": 4096,
|
| 15 |
+
"initializer_range": 0.02,
|
| 16 |
+
"intermediate_size": 12288,
|
| 17 |
+
"layer_types": [
|
| 18 |
+
"linear_attention",
|
| 19 |
+
"linear_attention",
|
| 20 |
+
"linear_attention",
|
| 21 |
+
"full_attention",
|
| 22 |
+
"linear_attention",
|
| 23 |
+
"linear_attention",
|
| 24 |
+
"linear_attention",
|
| 25 |
+
"full_attention",
|
| 26 |
+
"linear_attention",
|
| 27 |
+
"linear_attention",
|
| 28 |
+
"linear_attention",
|
| 29 |
+
"full_attention",
|
| 30 |
+
"linear_attention",
|
| 31 |
+
"linear_attention",
|
| 32 |
+
"linear_attention",
|
| 33 |
+
"full_attention",
|
| 34 |
+
"linear_attention",
|
| 35 |
+
"linear_attention",
|
| 36 |
+
"linear_attention",
|
| 37 |
+
"full_attention",
|
| 38 |
+
"linear_attention",
|
| 39 |
+
"linear_attention",
|
| 40 |
+
"linear_attention",
|
| 41 |
+
"full_attention",
|
| 42 |
+
"linear_attention",
|
| 43 |
+
"linear_attention",
|
| 44 |
+
"linear_attention",
|
| 45 |
+
"full_attention",
|
| 46 |
+
"linear_attention",
|
| 47 |
+
"linear_attention",
|
| 48 |
+
"linear_attention",
|
| 49 |
+
"full_attention"
|
| 50 |
+
],
|
| 51 |
+
"linear_conv_kernel_dim": 4,
|
| 52 |
+
"linear_key_head_dim": 128,
|
| 53 |
+
"linear_num_key_heads": 16,
|
| 54 |
+
"linear_num_value_heads": 32,
|
| 55 |
+
"linear_value_head_dim": 128,
|
| 56 |
+
"mamba_ssm_dtype": "float32",
|
| 57 |
+
"max_position_embeddings": 262144,
|
| 58 |
+
"mlp_only_layers": [],
|
| 59 |
+
"model_type": "qwen3_5_text",
|
| 60 |
+
"mtp_num_hidden_layers": 1,
|
| 61 |
+
"mtp_use_dedicated_embeddings": false,
|
| 62 |
+
"num_attention_heads": 16,
|
| 63 |
+
"num_hidden_layers": 32,
|
| 64 |
+
"num_key_value_heads": 4,
|
| 65 |
+
"pad_token_id": null,
|
| 66 |
+
"partial_rotary_factor": 0.25,
|
| 67 |
+
"rms_norm_eps": 1e-06,
|
| 68 |
+
"rope_parameters": {
|
| 69 |
+
"mrope_interleaved": true,
|
| 70 |
+
"mrope_section": [
|
| 71 |
+
11,
|
| 72 |
+
11,
|
| 73 |
+
10
|
| 74 |
+
],
|
| 75 |
+
"partial_rotary_factor": 0.25,
|
| 76 |
+
"rope_theta": 10000000,
|
| 77 |
+
"rope_type": "default"
|
| 78 |
+
},
|
| 79 |
+
"tie_word_embeddings": false,
|
| 80 |
+
"transformers_version": "5.14.1",
|
| 81 |
+
"use_cache": true,
|
| 82 |
+
"vocab_size": 248320
|
| 83 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"do_sample": true,
|
| 3 |
+
"eos_token_id": [
|
| 4 |
+
248046
|
| 5 |
+
],
|
| 6 |
+
"max_new_tokens": 900,
|
| 7 |
+
"pad_token_id": 248044,
|
| 8 |
+
"repetition_penalty": 1.05,
|
| 9 |
+
"temperature": 0.7,
|
| 10 |
+
"top_k": 20,
|
| 11 |
+
"top_p": 0.9,
|
| 12 |
+
"transformers_version": "5.14.1"
|
| 13 |
+
}
|
model-00001-of-00004.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1f63e1eeddb7c937a1c9e9f14d3525d81f00840326726cc61d2aa4074ac7fb99
|
| 3 |
+
size 4942706120
|
model-00002-of-00004.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:714cd49248612f422279689809c26b9bb3b51ab035d01260051008d9a89f776b
|
| 3 |
+
size 4987757928
|
model-00003-of-00004.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b69ddacf6aa02c75be83e1249c26b7019b07e5032044ba719915c18354cec308
|
| 3 |
+
size 4954810240
|
model-00004-of-00004.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:244bc973f37f78b44b71a4d01fb6de0e1cabc84563b28cd922b97a20a2432277
|
| 3 |
+
size 3022388120
|
model.safetensors.index.json
ADDED
|
@@ -0,0 +1,435 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
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|
|
|
|
|
|
|
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|
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|
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|
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|
|
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|
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|
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
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|
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tokenizer_config.json
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