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Model: JoaoZaokk/Qwen3-4B-Thinking-2507-Heretic-CodeFeedback Source: Original Platform
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README.md
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---
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license: other
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language:
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- en
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base_model:
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- JoaoZaokk/Qwen3-4B-Thinking-2507-MiniMax-M2.1-Distill-heretic
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base_model_relation: finetune
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- qwen3
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- text-generation
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- code
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- python
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- lora
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- qlora
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- safetensors
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- merged
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- heretic
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datasets:
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- iamtarun/python_code_instructions_18k_alpaca
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- m-a-p/CodeFeedback-Filtered-Instruction
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---
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# Qwen3 4B Thinking 2507 Heretic CodeFeedback
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This is a merged code-focused fine-tune based on:
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[`JoaoZaokk/Qwen3-4B-Thinking-2507-MiniMax-M2.1-Distill-heretic`](https://huggingface.co/JoaoZaokk/Qwen3-4B-Thinking-2507-MiniMax-M2.1-Distill-heretic)
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The model was trained with QLoRA/LoRA on Python and code instruction datasets, then merged back into the base model.
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This repository contains the **full merged safetensors model**, not only a LoRA adapter.
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## Base model
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| Item | Value |
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|---|---|
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| Base model | `JoaoZaokk/Qwen3-4B-Thinking-2507-MiniMax-M2.1-Distill-heretic` |
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| Architecture family | Qwen3 |
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| Parameter count | 4B |
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| Format | Hugging Face Transformers / safetensors |
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| Tensor type | F16 |
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| Fine-tuning method | QLoRA / LoRA |
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| Final state | Merged model |
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## Training datasets
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| Dataset | Samples used | Notes |
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|---|---:|---|
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| `iamtarun/python_code_instructions_18k_alpaca` | 5,000 | Python instruction/code examples |
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| `m-a-p/CodeFeedback-Filtered-Instruction` | 5,000 | Code instruction and feedback examples |
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A SWE-smith trajectory experiment was tested separately, but it was **not used** in this final merged version.
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## LoRA configuration
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| Parameter | Value |
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|---|---:|
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| LoRA rank | 16 |
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| LoRA alpha | 32 |
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| LoRA dropout | 0.05 |
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| Sequence length | 2048 |
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| Epochs per stage | 1 |
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| Quantized loading | 4-bit NF4 |
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| Trainable parameters | ~33M |
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| Trainable percentage | ~0.81% |
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Target modules:
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- `q_proj`
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- `k_proj`
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- `v_proj`
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- `o_proj`
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- `gate_proj`
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- `up_proj`
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- `down_proj`
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## Training stages
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| Stage | Input adapter | Dataset | Output adapter |
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|---|---|---|---|
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| 1 | Base model | Python instructions 5k | `heretic_F_lora_python_5000` |
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| 2 | `heretic_F_lora_python_5000` | CodeFeedback 5k | `heretic_F_lora_python5000_codefeedback5000` |
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| Final | Base model + final adapter | Merge | Full safetensors model |
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## Training environment
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| Component | Version |
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|---|---|
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| Python | 3.11 |
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| PyTorch | 2.11.0+cu128 |
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| CUDA | 12.8 |
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| Transformers | 5.10.2 |
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| Datasets | 5.0.0 |
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| Accelerate | 1.13.0 |
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| PEFT | 0.19.1 |
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| bitsandbytes | 0.49.2 |
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| sentencepiece | 0.2.1 |
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| tiktoken | 0.13.0 |
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| protobuf | 7.35.0 |
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| pandas | 3.0.3 |
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| pyarrow | 24.0.0 |
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Training GPU:
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- NVIDIA GeForce RTX 3080 Ti 12 GB
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## Intended use
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This model is intended for local experimentation with:
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- Python code generation
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- code explanation
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- simple debugging
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- instruction-following tests
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- downstream conversion to GGUF, AWQ, GPTQ, or OpenVINO formats
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## Notes
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This is an experimental model. It may produce incorrect code, unsafe suggestions, or hallucinated explanations. Outputs should be reviewed before use in production or security-sensitive environments.
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## Hardware compatibility estimate
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This table is an approximate guide for the current **merged F16 safetensors** version.
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| Hardware / VRAM | Status | Notes |
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|---|---|---|
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| 6 GB VRAM | 🔴 Unlikely | F16 weights are too large without heavy offload or quantization. |
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| 8 GB VRAM | 🔴 Very tight | May fail or require CPU offload. Use GGUF/AWQ/INT4 instead. |
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| 10 GB VRAM | 🟡 Possible | May run with low context and careful memory settings. |
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| 12 GB VRAM | 🟢 Likely | Tested training/inference workflow on RTX 3080 Ti 12 GB with 4-bit loading. |
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| 16 GB VRAM | 🟢 Good | Comfortable for normal local inference. |
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| 24 GB VRAM | 🟢 Very good | Recommended for larger context, conversion, quantization, and experiments. |
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| 32 GB+ RAM CPU-only | 🟡 Possible | Slow. Better with GGUF quantized versions. |
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### Quantized versions
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Planned/recommended export formats:
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| Format | Status | Expected use |
|
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|---|---|---|
|
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| F16 safetensors | 🟢 Current | Full merged model, best source for conversion. |
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| AWQ 4-bit | 🟡 Planned | Better for GPU/server inference, mainly CUDA/Linux or compatible runtimes. |
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| OpenVINO INT4 / AWQ-style compression | 🟢 Planned for Intel Arc | Recommended path for Intel Arc/OpenVINO. |
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| GGUF Q5_K_M / Q6_K / Q8_0 | 🟡 Planned | Recommended for LM Studio, llama.cpp, Ollama, CPU/GPU mixed inference. |
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### Practical recommendation
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For this repository, use the current F16 safetensors model as the **master model**.
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For actual local use:
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- RTX 3080 Ti 12 GB or better: F16 may work, but quantized versions are preferred.
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- RTX 3090 24 GB: F16 and quantization workflows are much more comfortable.
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- Intel Arc: convert this model to OpenVINO INT4 instead of using CUDA-focused AWQ.
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- Low VRAM systems: wait for GGUF or INT4 builds.
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88
chat_template.jinja
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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 + '\n\n' }}
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{%- endif %}
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{{- "# 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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{%- endif %}
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{%- endif %}
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
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{%- for message in messages[::-1] %}
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{%- set index = (messages|length - 1) - loop.index0 %}
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{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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{%- set ns.multi_step_tool = false %}
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{%- set ns.last_query_index = index %}
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{%- endif %}
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{%- endfor %}
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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{%- set reasoning_content = '' %}
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{%- if message.reasoning_content is string %}
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{%- set reasoning_content = message.reasoning_content %}
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{%- else %}
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{%- if '</think>' in content %}
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{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
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{%- set content = content.split('</think>')[-1].lstrip('\n') %}
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{%- endif %}
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{%- endif %}
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{%- if loop.index0 > ns.last_query_index %}
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{%- if loop.last or (not loop.last and reasoning_content) %}
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{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
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{%- else %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- endif %}
|
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{%- if message.tool_calls %}
|
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
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{{- '\n' }}
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{%- endif %}
|
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{%- if tool_call.function %}
|
||||
{%- set tool_call = tool_call.function %}
|
||||
{%- endif %}
|
||||
{{- '<tool_call>\n{"name": "' }}
|
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{{- tool_call.name }}
|
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{{- '", "arguments": ' }}
|
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{%- if tool_call.arguments is string %}
|
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
|
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{%- endif %}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{%- endif %}
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{{- '<|im_end|>\n' }}
|
||||
{%- elif message.role == "tool" %}
|
||||
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
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{{- '<|im_start|>user' }}
|
||||
{%- endif %}
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||||
{{- '\n<tool_response>\n' }}
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{{- content }}
|
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{{- '\n</tool_response>' }}
|
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
||||
{{- '<|im_end|>\n' }}
|
||||
{%- endif %}
|
||||
{%- endif %}
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||||
{%- endfor %}
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{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant
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<think>
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' }}
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{%- endif %}
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73
config.json
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config.json
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{
|
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"architectures": [
|
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"Qwen3ForCausalLM"
|
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],
|
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"attention_bias": false,
|
||||
"attention_dropout": 0.0,
|
||||
"bos_token_id": null,
|
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"dtype": "float16",
|
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"eos_token_id": 151645,
|
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"head_dim": 128,
|
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"hidden_act": "silu",
|
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"hidden_size": 2560,
|
||||
"initializer_range": 0.02,
|
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"intermediate_size": 9728,
|
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"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"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",
|
||||
"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",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention"
|
||||
],
|
||||
"max_position_embeddings": 262144,
|
||||
"max_window_layers": 36,
|
||||
"model_type": "qwen3",
|
||||
"num_attention_heads": 32,
|
||||
"num_hidden_layers": 36,
|
||||
"num_key_value_heads": 8,
|
||||
"pad_token_id": 151654,
|
||||
"rms_norm_eps": 1e-06,
|
||||
"rope_parameters": {
|
||||
"rope_theta": 5000000,
|
||||
"rope_type": "default"
|
||||
},
|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
||||
"transformers_version": "5.10.2",
|
||||
"unsloth_fixed": true,
|
||||
"unsloth_version": "2025.12.5",
|
||||
"use_cache": true,
|
||||
"use_sliding_window": false,
|
||||
"vocab_size": 151936
|
||||
}
|
||||
7
generation_config.json
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7
generation_config.json
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||||
{
|
||||
"_from_model_config": true,
|
||||
"eos_token_id": 151645,
|
||||
"pad_token_id": 151654,
|
||||
"transformers_version": "5.10.2",
|
||||
"use_cache": true
|
||||
}
|
||||
3
model-00001-of-00003.safetensors
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3
model-00001-of-00003.safetensors
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size 3981503976
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3
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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size 102247928
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406
model.safetensors.index.json
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406
model.safetensors.index.json
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|
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{
|
||||
"metadata": {
|
||||
"total_parameters": 4022468096,
|
||||
"total_size": 8044936192
|
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|
||||
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|
||||
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|
||||
"model.layers.0.input_layernorm.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.0.mlp.down_proj.weight": "model-00001-of-00003.safetensors",
|
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"model.layers.0.mlp.gate_proj.weight": "model-00001-of-00003.safetensors",
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"model.layers.0.mlp.up_proj.weight": "model-00001-of-00003.safetensors",
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"model.layers.0.post_attention_layernorm.weight": "model-00001-of-00003.safetensors",
|
||||
"model.layers.0.self_attn.k_norm.weight": "model-00001-of-00003.safetensors",
|
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"model.layers.0.self_attn.k_proj.weight": "model-00001-of-00003.safetensors",
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"model.layers.0.self_attn.o_proj.weight": "model-00001-of-00003.safetensors",
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12
requirements-training.txt
Normal file
12
requirements-training.txt
Normal file
@@ -0,0 +1,12 @@
|
||||
python==3.11
|
||||
torch==2.11.0+cu128
|
||||
transformers==5.10.2
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datasets==5.0.0
|
||||
accelerate==1.13.0
|
||||
peft==0.19.1
|
||||
bitsandbytes==0.49.2
|
||||
sentencepiece==0.2.1
|
||||
tiktoken==0.13.0
|
||||
protobuf==7.35.0
|
||||
pandas==3.0.3
|
||||
pyarrow==24.0.0
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:035e84034e240f0aea24a0c034801801d23ac0506250099f017982ec808ac7d3
|
||||
size 11422818
|
||||
19
tokenizer_config.json
Normal file
19
tokenizer_config.json
Normal file
@@ -0,0 +1,19 @@
|
||||
{
|
||||
"add_prefix_space": false,
|
||||
"backend": "tokenizers",
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"is_local": true,
|
||||
"local_files_only": false,
|
||||
"max_length": null,
|
||||
"model_max_length": 262144,
|
||||
"pad_to_multiple_of": null,
|
||||
"pad_token": "<|vision_pad|>",
|
||||
"pad_token_type_id": 0,
|
||||
"padding_side": "left",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
Reference in New Issue
Block a user