commit 63c3d2c12f44885374fe696af1d8765202088860 Author: ModelHub XC Date: Sat Jun 27 10:32:16 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: codestrate/Llama3.2-3B-Claude-Reasoning-Distill Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..21f2655 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,43 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text +Llama-3.2-3B-Instruct.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text +Llama-3b-ft-claude-merged.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text +Llama-3b-ft-claude-merged.BF16.gguf filter=lfs diff=lfs merge=lfs -text +Llama-3b-ft-claude-merged.F16.gguf filter=lfs diff=lfs merge=lfs -text +Llama-3b-ft-claude-merged.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text +Llama3.2-3B-Claude-Reasoning-Distill.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text +Llama3.2-3B-Claude-Reasoning-Distill.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text +loss_curve_with_rolling_average.png filter=lfs diff=lfs merge=lfs -text diff --git a/Llama-3b-ft-claude-merged.F16.gguf b/Llama-3b-ft-claude-merged.F16.gguf new file mode 100644 index 0000000..b3d8015 --- /dev/null +++ b/Llama-3b-ft-claude-merged.F16.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:23c0c74fba891ba6616e433900907c5142735360fe52803bb5d4154659ac6580 +size 6433700256 diff --git a/Llama3.2-3B-Claude-Reasoning-Distill.Q4_K_M.gguf b/Llama3.2-3B-Claude-Reasoning-Distill.Q4_K_M.gguf new file mode 100644 index 0000000..adba807 --- /dev/null +++ b/Llama3.2-3B-Claude-Reasoning-Distill.Q4_K_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dda4cd569d793655aa9fe13fe1b7b7f1a5ea440ee88630bc247a3763b9fb214d +size 2019382624 diff --git a/Llama3.2-3B-Claude-Reasoning-Distill.Q8_0.gguf b/Llama3.2-3B-Claude-Reasoning-Distill.Q8_0.gguf new file mode 100644 index 0000000..8322527 --- /dev/null +++ b/Llama3.2-3B-Claude-Reasoning-Distill.Q8_0.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:673f24508da633866b3358c4b2d83b60bb250c5ad8a59ce757458c6eba37b163 +size 3421905696 diff --git a/Modelfile b/Modelfile new file mode 100644 index 0000000..45d407a --- /dev/null +++ b/Modelfile @@ -0,0 +1,62 @@ +FROM Llama3.2-3B-Claude-Reasoning-Distill.Q4_K_M.gguf + +SYSTEM "You are a helpful assistant. Before giving your final answer, reason through the problem inside ... tags. Close the thinking block and then give your final answer." + +TEMPLATE """{{ if .Messages }} +{{- if or .System .Tools }}<|start_header_id|>system<|end_header_id|> +{{- if .System }} + +{{ .System }} +{{- end }} +{{- if .Tools }} + +You are a helpful assistant with tool calling capabilities. When you receive a tool call response, use the output to format an answer to the original use question. +{{- end }} +{{- end }}<|eot_id|> +{{- range $i, $_ := .Messages }} +{{- $last := eq (len (slice $.Messages $i)) 1 }} +{{- if eq .Role "user" }}<|start_header_id|>user<|end_header_id|> +{{- if and $.Tools $last }} + +Given the following functions, please respond with a JSON for a function call with its proper arguments that best answers the given prompt. + +Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. Do not use variables. + +{{ $.Tools }} +{{- end }} + +{{ .Content }}<|eot_id|>{{ if $last }}<|start_header_id|>assistant<|end_header_id|> + +{{ end }} +{{- else if eq .Role "assistant" }}<|start_header_id|>assistant<|end_header_id|> +{{- if .ToolCalls }} + +{{- range .ToolCalls }}{"name": "{{ .Function.Name }}", "parameters": {{ .Function.Arguments }}}{{ end }} +{{- else }} + +{{ .Content }}{{ if not $last }}<|eot_id|>{{ end }} +{{- end }} +{{- else if eq .Role "tool" }}<|start_header_id|>ipython<|end_header_id|> + +{{ .Content }}<|eot_id|>{{ if $last }}<|start_header_id|>assistant<|end_header_id|> + +{{ end }} +{{- end }} +{{- end }} +{{- else }} +{{- if .System }}<|start_header_id|>system<|end_header_id|> + +{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|> + +{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|> + +{{ end }}{{ .Response }}{{ if .Response }}<|eot_id|>{{ end }}""" + +PARAMETER stop "<|start_header_id|>" +PARAMETER stop "<|end_header_id|>" +PARAMETER stop "<|eot_id|>" +PARAMETER stop "<|eom_id|>" +PARAMETER temperature 0.7 +PARAMETER repeat_penalty 1.3 +PARAMETER min_p 0.1 +PARAMETER num_predict 1024 diff --git a/README.md b/README.md new file mode 100644 index 0000000..a1f13a8 --- /dev/null +++ b/README.md @@ -0,0 +1,213 @@ +--- +tags: +- gguf +- llama.cpp +- unsloth +- llama +- llama3.2 +- distillation +- reasoning +- fine-tuning +license: llama3.2 +datasets: +- angrygiraffe/claude-opus-4.6-4.7-reasoning-8.7k +language: +- en +base_model: +- unsloth/Llama-3.2-3B-Instruct-bnb-4bit +pipeline_tag: text-generation +library_name: transformers +--- + +# Llama 3.2 3B — Claude Reasoning Distill + +This model was a second attempt at reasoning distillation, with several fixes from the 1B run — but the core approach was still wrong. + +**1. Same root problem: SFT copies style, not capability** - GRPO is the right approach + +**2. Dataset truncation caused the stopping problem** +The training dataset (`angrygiraffe/claude-opus-4.6-4.7-reasoning-8.7k`) averages ~1,954 tokens per example, with p90 assistant responses alone hitting ~1,760 tokens. Trained at `seq_len=2048`, a significant portion of examples were silently truncated — cutting off the `<|eot_id|>` end-of-turn token before it could be written. +The model learned from many examples that responses don't need to end. This is a dataset fit problem, not a model problem. + +**3. Wrong EOS token at inference** +Llama 3 has two EOS-like tokens. `tokenizer.eos_token_id` returns `128001` (`<|end_of_text|>`), but the model generates `128009` (`<|eot_id|>`) to end a turn. The default `model.generate()` call never passes `128009`, so generation runs until `max_new_tokens`. This compounds the truncation issue above. + +**Same Fix as 1B if you're using this model:** + +```python +model.generate( + input_ids=inputs, + eos_token_id=[128001, 128009], + max_new_tokens=512, + repetition_penalty=1.3, + no_repeat_ngram_size=6, +) +``` + +For Ollama, add to your Modelfile: + +``` +PARAMETER stop "<|eot_id|>" +PARAMETER stop "<|end_of_text|>" +``` +--- +An updated attempt at distilling Claude Opus 4.6/4.7 reasoning traces into a small-form-factor model. The predecessor [Llama 3.2 1B Claude Opus Reasoning Distill](https://huggingface.co/codestrate/Llama3.2-1B-Claude-Opus-Reasoning-Distill) demonstrated that a 1B model could adopt `` blocks but suffered from echolalia and a GSM8K regression. This run addresses the two root causes identified from that experiment: + +1. **Capacity** — 3B sits closer to the parameter floor where structured reasoning adoption is viable, as seen in models like [Gemma 4 E2B-IT](https://huggingface.co/google/gemma-4-E2B-it) and [Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B) (which has `` baked into pretraining) +2. **Token boundaries** — `` and `` are registered as special tokens (vocab 128256 → 128258) with trained embeddings, giving the model a hard mode boundary instead of treating them as plain text +3. **Training on Reponses Only** - Unlike 1B run, I used the `train_on_responses_only` from `unsloth` to mask out user inputs to have a accuracy increase in multi-turn conversational fine tuning. + +> **Benchmarks will not be available.** +--- + +## Model Details + +| Field | Value | +|---|---| +| **Base model** | [`unsloth/Llama-3.2-3B-Instruct-bnb-4bit`](https://huggingface.co/unsloth/Llama-3.2-3B-Instruct-bnb-4bit) | +| **Model type** | Causal LM — LoRA adapter (PEFT) on Llama-3.2-3B-Instruct | +| **Language** | English | +| **License** | [Meta Llama 3.2 Community License](https://www.llama.com/llama3_2/license/) | +| **Training framework** | Unsloth + TRL SFTTrainer | +| **Hardware** | Tesla T4 (Kaggle) | +| **Max sequence length** | 2048 | + +--- + +## Intended Use + +Generating step-by-step reasoning traces (`` blocks) followed by final answers across a broad range of instruction-following tasks. Useful for studying how reasoning distillation scales to sub-4B models and how registered thinking tokens affect small-model behaviour. + +**Not intended for:** production use, mathematical proofs requiring reliability, or replacing a larger reasoning model. Benchmark regressions vs base are expected until verified otherwise. + +--- + +## How to Get Started + +### From the adapter + +The LoRA adapter is available separately — load it on top of the base model without downloading the full merged weights. + +> **Important:** load the tokenizer from the adapter directory, not the base model. The adapter tokenizer carries the correct 128258-token vocabulary with ``/`` baked in. Using the base model tokenizer (128256) will cause an embedding dimension mismatch. + +```python +from unsloth import FastLanguageModel +from transformers import AutoTokenizer, TextStreamer +from peft import PeftModel + +ADAPTER_PATH = "codestrate/Llama3.2-3B-Claude-Reasoning-Distill" + +model, _ = FastLanguageModel.from_pretrained( + model_name="unsloth/Llama-3.2-3B-Instruct-bnb-4bit", + load_in_4bit=True, + max_seq_length=2048, +) +tokenizer = AutoTokenizer.from_pretrained(ADAPTER_PATH) # vocab=128258 +model.resize_token_embeddings(len(tokenizer)) +model = PeftModel.from_pretrained(model, ADAPTER_PATH) +FastLanguageModel.for_inference(model) + +SYSTEM_PROMPT = "You are a helpful assistant. Think step by step inside ... before giving your final answer." +messages = [ + {"role": "system", "content": SYSTEM_PROMPT}, + {"role": "user", "content": "Write a Python function to check if a number is prime."}, +] +inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to("cuda") + +streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True) +_ = model.generate( + input_ids=inputs, + streamer=streamer, + max_new_tokens=1024, + temperature=0.7, + min_p=0.1, + repetition_penalty=1.3, + no_repeat_ngram_size=6, + use_cache=True, +) +``` + +### From GGUF (Ollama / LM Studio) + +A Modelfile is included for Ollama. For direct use: + +``` +ollama run hf.co/codestrate/Llama3.2-3B-Claude-Reasoning-Distill:Q4_K_M +``` + +--- + +## Training Details + +### Dataset + +[`angrygiraffe/claude-opus-4.6-4.7-reasoning-8.7k`](https://huggingface.co/datasets/angrygiraffe/claude-opus-4.6-4.7-reasoning-8.7k) — `instruct_train.jsonl` split (full instruct + reasoning, ~7,700 examples). Data already in OpenAI messages format; mapped directly through `apply_chat_template` with no additional preprocessing. + +The previous 1B run used only the `coding` + `math` categories (~2,000 examples). This run uses the full instruct split for broader coverage. + +### Hyperparameters + +| Parameter | Value | +|---|---| +| LoRA Rank / Alpha | 32 / 64 | +| Target Modules | All | +| Sequence Length | 2048 | +| Effective Batch | 16 (2 × grad_accum 8) | +| Steps | 904 (~2 epochs) | +| Learning Rate | 1e-4 / cosine | +| Warmup Steps | 50 | +| Optimizer | adamw_8bit | +| Weight Decay | 0.01 | +| Precision | bfloat16 | + +### Loss Curve + +![Loss Curve](loss_curve_with_rolling_average.png) + +| Step | Loss | Step | Loss | Step | Loss | +|---|---|---|---|---|---| +| 50 | 2.1372 | 350 | 1.8798 | 650 | 1.7567 | +| 100 | 1.9597 | 400 | 1.8512 | 700 | 1.7530 | +| 150 | 1.9251 | 450 | 1.8493 | 750 | **1.7391** | +| 200 | 1.8972 | 500 | 1.7670 | 800 | 1.7709 | +| 250 | 1.8891 | 550 | 1.7707 | 850 | 1.7401 | +| 300 | 1.8738 | 600 | 1.7668 | 900 | 1.7598 | + +Drop: 2.14 → 1.74 (~0.40 absolute). Visible cross-epoch improvement at step ~452 (−0.082). Plateau reached in epoch 2 from step 750 — a third epoch would not have been beneficial on this dataset. + +--- + +## Known Limitations + +- **Benchmarks not yet available** — results will be added when the evaluation runs complete +- **Echolalia / repetition** — reduced vs the 1B run due to special token boundaries, but not eliminated; `repetition_penalty=1.3` and `no_repeat_ngram_size=6` are recommended at inference (needs more testing) +- **System prompt required** — without the `...` contract in the system prompt, the model may not cleanly transition from reasoning block to final answer +- **Not a production model** — a research artefact studying reasoning distillation at sub-4B scale + +--- + +## Available Files + +| File | Format | Use | +|---|---|---| +| `Llama-3.2-3B-Claude-Reasoning-Distill.Q4_K_M.gguf` | GGUF Q4_K_M | LM Studio / Ollama (recommended) | +| `Llama-3.2-3B-Claude-Reasoning-Distill.Q8_0.gguf` | GGUF Q8 | Higher fidelity inference (near lossless; still lightweight)| +| `Llama-3.2-3B-Claude-Reasoning-Distill.F16.gguf` | GGUF F16 | Full precision GGUF | +| Adapter (`adapter_model.safetensors`) | LoRA adapter | PEFT inference / further fine-tuning | + +--- + +## Framework Versions + +- Python 3.12.13 +- Unsloth 2026.5.8 +- PEFT 0.19.1 +- TRL 0.24.0 +- PyTorch 2.10.0+cu128 +- Transformers 4.47.1 + +--- + +*Predecessor: [Llama3.2-1B-Claude-Opus-Reasoning-Distill](https://huggingface.co/codestrate/Llama3.2-1B-Claude-Opus-Reasoning-Distill)* +*Trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth)* +[](https://github.com/unslothai/unsloth) diff --git a/config.json b/config.json new file mode 100644 index 0000000..74756a8 --- /dev/null +++ b/config.json @@ -0,0 +1,38 @@ +{ + "architectures": [ + "LlamaForCausalLM" + ], + "attention_bias": false, + "attention_dropout": 0.0, + "bos_token_id": 128000, + "dtype": "float16", + "eos_token_id": 128009, + "head_dim": 128, + "hidden_act": "silu", + "hidden_size": 3072, + "initializer_range": 0.02, + "intermediate_size": 8192, + "max_position_embeddings": 131072, + "mlp_bias": false, + "model_type": "llama", + "num_attention_heads": 24, + "num_hidden_layers": 28, + "num_key_value_heads": 8, + "pad_token_id": 128004, + "pretraining_tp": 1, + "rms_norm_eps": 1e-05, + "rope_parameters": { + "factor": 32.0, + "high_freq_factor": 4.0, + "low_freq_factor": 1.0, + "original_max_position_embeddings": 8192, + "rope_theta": 500000.0, + "rope_type": "llama3" + }, + "tie_word_embeddings": true, + "transformers_version": "5.5.0", + "unsloth_fixed": true, + "unsloth_version": "2026.5.8", + "use_cache": true, + "vocab_size": 128258 +} diff --git a/generation_config.json b/generation_config.json new file mode 100644 index 0000000..c8ae05a --- /dev/null +++ b/generation_config.json @@ -0,0 +1,9 @@ +{ + "do_sample": true, + "max_new_tokens": 1024, + "min_p": 0.1, + "no_repeat_ngram_size": 6, + "repetition_penalty": 1.3, + "temperature": 0.7, + "transformers_version": "5.5.0" +} diff --git a/loss_curve_with_rolling_average.png b/loss_curve_with_rolling_average.png new file mode 100644 index 0000000..f34a991 --- /dev/null +++ b/loss_curve_with_rolling_average.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:41d8d767c5d5621feb0573e489e60ceb61c0cfa22adc1837ae46a713ecac57ef +size 135182