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Model: ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth Source: Original Platform
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README.md
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README.md
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---
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license: mit
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- unsloth
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- qwen2
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- sft
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- fine-tuned
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- trl
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- lora
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- qlora
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- text-generation
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- reasoning
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- conversational
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base_model: WeiboAI/VibeThinker-3B
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datasets:
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- ermiaazarkhalili/claude-reasoning-distillation
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model-index:
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- name: VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth
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results: []
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---
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# VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth
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This model is a fine-tuned version of [VibeThinker-3B](https://huggingface.co/WeiboAI/VibeThinker-3B) optimized for **reasoning distillation (chain-of-thought)** using [Unsloth](https://github.com/unslothai/unsloth) for **2x faster training** and **60% less VRAM**.
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Trained on the [claude-reasoning-distillation](https://huggingface.co/datasets/ermiaazarkhalili/claude-reasoning-distillation) dataset, which contains 10,477 samples of Claude's reasoning traces with `<think>` blocks for chain-of-thought learning.
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## Overview
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| Property | Value |
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|----------|-------|
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| **Developed by** | [ermiaazarkhalili](https://huggingface.co/ermiaazarkhalili) |
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| **License** | MIT |
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| **Language** | English |
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| **Base Model** | [VibeThinker-3B](https://huggingface.co/WeiboAI/VibeThinker-3B) |
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| **Model Size** | 3B parameters |
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| **Training Framework** | [Unsloth](https://github.com/unslothai/unsloth) + [TRL](https://github.com/huggingface/trl) |
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| **Training Method** | SFT with QLoRA (4-bit) |
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| **Context Length** | 2,048 tokens |
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| **GGUF Available** | [VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF](https://huggingface.co/ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF) |
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## Training Configuration
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### SFT + LoRA Settings
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| Parameter | Value |
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|-----------|-------|
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| Unsloth Class | `FastLanguageModel` |
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| Chat Template | built-in VibeThinker (Qwen2) |
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| Learning Rate | 2e-4 |
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| Batch Size | 2 per device |
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| Gradient Accumulation | 4 steps |
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| Effective Batch Size | 8 |
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| Max Steps | 1 epoch (full dataset) |
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| Optimizer | AdamW 8-bit |
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| LR Scheduler | Linear |
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| Warmup Steps | 5 |
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| Precision | Auto (BF16/FP16) |
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| Gradient Checkpointing | Enabled (Unsloth optimized) |
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| Seed | 3407 |
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### LoRA Configuration
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| Parameter | Value |
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|-----------|-------|
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| LoRA Rank (r) | 16 |
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| LoRA Alpha | 16 |
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| LoRA Dropout | 0 |
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| Quantization | 4-bit QLoRA |
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| Target Modules | q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj |
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### Dataset
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| Property | Value |
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|----------|-------|
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| Dataset | [Claude Reasoning Distillation](https://huggingface.co/datasets/ermiaazarkhalili/claude-reasoning-distillation) |
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| Training Samples | 10,477 |
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| Format | Messages with `thinking` field for chain-of-thought |
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### Hardware
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| Property | Value |
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|----------|-------|
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| GPU | NVIDIA H100 80GB HBM3 (MIG 3g.40gb slice) |
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| Cluster | DRAC Fir (Compute Canada) |
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| Execution | [Papermill](https://github.com/nteract/papermill) on SLURM |
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### Training Outcome
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| Metric | Value |
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|--------|-------|
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| SLURM Job ID | `45169145` |
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| Runtime | 23m 49s (1429s) |
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| Final Training Loss | 1.367 |
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| Peak VRAM | 12.66 GB |
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| GPU | H100 80GB HBM3 (MIG 3g.40gb) |
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## Usage
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### Quick Start (Transformers)
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model_id = "ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.bfloat16,
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device_map="auto",
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)
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messages = [
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{"role": "user", "content": "Solve step by step: What is the sum of the first 10 prime numbers?"}
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]
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text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer(text, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7, do_sample=True)
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response = tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True)
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print(response)
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```
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### Using with Unsloth (Fastest)
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```python
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from unsloth import FastLanguageModel
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model, tokenizer = FastLanguageModel.from_pretrained(
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"ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth",
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max_seq_length=2048,
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load_in_4bit=True,
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)
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```
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### 4-bit Quantized Inference
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```python
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from transformers import AutoModelForCausalLM, BitsAndBytesConfig
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import torch
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quantization_config = BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_compute_dtype=torch.bfloat16,
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bnb_4bit_use_double_quant=True,
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bnb_4bit_quant_type="nf4",
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)
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model = AutoModelForCausalLM.from_pretrained(
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"ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth",
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quantization_config=quantization_config,
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device_map="auto",
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)
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```
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## GGUF Versions
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Quantized GGUF versions for CPU and edge inference are available at:
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**[VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF](https://huggingface.co/ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF)**
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| Format | Description |
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|--------|-------------|
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| `Q4_K_M` | Recommended — good balance of quality and size |
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| `Q5_K_M` | Higher quality, slightly larger |
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| `Q8_0` | Near-lossless, largest GGUF size |
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### Using with Ollama
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```bash
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ollama pull hf.co/ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF:Q4_K_M
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ollama run hf.co/ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth-GGUF:Q4_K_M "Solve step by step: What is the sum of the first 10 prime numbers?"
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```
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### Using with llama.cpp
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```bash
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./llama-cli -m VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth-Q4_K_M.gguf -p "Solve step by step: What is the sum of the first 10 prime numbers?" -n 512
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```
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## Limitations
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- **Language**: Primarily trained on English data
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- **Knowledge Cutoff**: Limited to base model's training data cutoff
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- **Hallucinations**: May generate plausible-sounding but incorrect information
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- **Context Length**: Fine-tuned with 2,048 token context window
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- **Safety**: Not extensively safety-tuned; use with appropriate guardrails
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## Training Framework Versions
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| Package | Version |
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|---------|---------|
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| Unsloth | 2026.4.4 |
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| TRL | 0.24.0 |
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| Transformers | 5.5.0 |
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| PyTorch | 2.9.0 |
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| Datasets | 4.3.0 |
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| PEFT | 0.18.1 |
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| BitsAndBytes | 0.49.2 |
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## Citation
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```bibtex
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@misc{ermiaazarkhalili_vibethinker_3b_sft_claude_opus_reasoning_unsloth,
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author = {ermiaazarkhalili},
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title = {VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth: Fine-tuned VibeThinker-3B with Unsloth},
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year = {2026},
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publisher = {Hugging Face},
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howpublished = {\url{https://huggingface.co/ermiaazarkhalili/VibeThinker-3B-SFT-Claude-Opus-Reasoning-Unsloth}}
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}
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```
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## Acknowledgments
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- [Unsloth](https://github.com/unslothai/unsloth) for 2x faster fine-tuning
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- Base model developers (WeiboAI)
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- [Hugging Face TRL Team](https://github.com/huggingface/trl) for the training library
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- [Claude Reasoning Distillation](https://huggingface.co/datasets/ermiaazarkhalili/claude-reasoning-distillation) dataset
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- [Compute Canada / DRAC](https://alliancecan.ca/) for HPC resources
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chat_template.jinja
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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 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 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 %}
|
||||
{%- endif %}
|
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{%- endfor %}
|
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{%- if add_generation_prompt %}
|
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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config.json
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config.json
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{
|
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"architectures": [
|
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"Qwen2ForCausalLM"
|
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],
|
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"attention_dropout": 0.0,
|
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"bos_token_id": null,
|
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"torch_dtype": "bfloat16",
|
||||
"eos_token_id": 151643,
|
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"hidden_act": "silu",
|
||||
"hidden_size": 2048,
|
||||
"initializer_range": 0.02,
|
||||
"intermediate_size": 11008,
|
||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"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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"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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"full_attention",
|
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"full_attention",
|
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"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 131072,
|
||||
"max_window_layers": 36,
|
||||
"model_type": "qwen2",
|
||||
"num_attention_heads": 16,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 2,
|
||||
"pad_token_id": 151667,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_parameters": {
|
||||
"rope_theta": 1000000.0,
|
||||
"rope_type": "default"
|
||||
},
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"unsloth_version": "2026.4.6",
|
||||
"use_cache": false,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
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3
model-00001-of-00002.safetensors
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model-00001-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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size 4957560304
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3
model-00002-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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size 1214366696
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441
model.safetensors.index.json
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441
model.safetensors.index.json
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{
|
||||
"metadata": {
|
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"total_size": 6171877376
|
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},
|
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"weight_map": {
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|
||||
"model.norm.weight": "model-00002-of-00002.safetensors"
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:d5575c5e06b18e034822c854ab6bf1739aceba71807c3957b6632431468b9eca
|
||||
size 11422727
|
||||
16
tokenizer_config.json
Normal file
16
tokenizer_config.json
Normal file
@@ -0,0 +1,16 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"backend": "tokenizers",
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|endoftext|>",
|
||||
"errors": "replace",
|
||||
"is_local": false,
|
||||
"model_max_length": 131072,
|
||||
"pad_token": "<|PAD_TOKEN|>",
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null,
|
||||
"chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are a helpful assistant.' }}\n {%- endif %}\n {{- \"\\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>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\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\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are a helpful assistant.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n"
|
||||
}
|
||||
Reference in New Issue
Block a user