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Model: md896/sql-debug-agent-qwen25-05b-grpo-wandb-continue-v2 Source: Original Platform
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---
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language:
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- en
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- text-generation
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- conversational
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- qwen2
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- trl
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- grpo
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- safetensors
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- text-generation-inference
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base_model:
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- Qwen/Qwen2.5-Coder-0.5B-Instruct
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- Qwen/Qwen2.5-Coder-7B-Instruct
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model-index:
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- name: sql-debug-agent-qwen25-05b-grpo-wandb-continue-v2
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results:
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- task:
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type: text-generation
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name: SQL Repair (Execution-Grounded)
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dataset:
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type: openenv-sql-debug
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name: SQL Debug Environment task suite
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metrics:
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- type: spider_style_headline
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value: 78.5
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name: Spider-style headline
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---
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# Model Card for `md896/sql-debug-agent-qwen25-05b-grpo-wandb-continue-v2`
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## Model Details
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| Field | Value |
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|---|---|
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| Developed by | Md Ayan (`mdayan8`) |
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| Model type | Causal LM fine-tuning workflow for SQL debugging/repair |
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| Language | English (SQL + natural language prompts) |
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| License | Apache-2.0 |
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| Shared by | `md896` |
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| Pipeline tag | Text Generation |
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| Model family tags | `qwen2`, `trl`, `grpo`, `conversational`, `text-generation-inference` |
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## Model Description
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This model is part of an execution-grounded SQL debugging workflow built on OpenEnv tasks. The key idea is to optimize for runtime correctness rather than only text-level plausibility.
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The training/evaluation workflow uses:
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1. A fast bridge phase on **Qwen2.5-Coder-0.5B-Instruct** for environment wiring checks.
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2. Baseline/eval track with **Qwen2.5-Coder-7B-Instruct** and benchmark comparisons.
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3. GRPO-based optimization signals from SQL execution outcomes, grader feedback, and task completion behavior.
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## Model Sources
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- Repository: https://github.com/mdayan8/sql-debug-env
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- Demo / Environment: https://md896-sql-debug-env.hf.space
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- Training dashboard (W&B): https://wandb.ai/mdayanbag-pesitm/sql-debug-grpo-best-budget/workspace?nw=nwusermdayanbag
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- Reference arXiv listed for metadata context: https://arxiv.org/abs/1910.09700
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## Intended Uses
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### Direct Use
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- SQL repair assistant style prompting in controlled environments
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- Runtime-evaluated SQL correction experiments
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- Benchmark comparison against deterministic SQL debugging tasks
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### Downstream Use
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- Fine-tuning initialization for enterprise SQL repair use cases
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- Evaluation baseline for OpenEnv-style SQL agents
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### Out-of-Scope / Not Recommended
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- Autonomous execution against production databases without guardrails
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- High-risk environments requiring strict SQL governance without additional review controls
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## Training Details
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### Training Data
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Training signals are generated from deterministic OpenEnv SQL debugging tasks using reset/step interaction loops and execution-based grading.
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### Training Procedure
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| Step | Description |
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|---|---|
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| Session isolation | Every episode runs in isolated in-memory SQLite state |
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| Task iteration | Query proposals are evaluated task-by-task under deterministic graders |
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| GRPO objective | Relative ranking over generated candidates using execution-grounded reward |
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| Artifact capture | Run metrics, reward traces, and charts are persisted and published |
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### Key Training Hyperparameters (workflow-level)
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| Hyperparameter area | Value / behavior |
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|---|---|
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| GRPO generations | Configured `>= 2` (runtime-safe default in launcher) |
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| Reward composition | Correctness + efficiency + progress + schema bonus - penalties |
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| Sampling controls | Temperature / top-p / completion length controlled in training scripts |
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For script-level specifics, see:
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- `ultimate_sota_training.py`
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- `launch_job.py`
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## Evaluation
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### Metrics Snapshot
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| Metric | Value |
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|---|---:|
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| Spider-style industry baseline | 48.2% |
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| Qwen-7B base | 52.4% |
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| RL agent headline | 78.5% |
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| Performance leap view | 0.0% -> 25.0% |
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| Eval artifact pass | 32-run |
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### Benchmark Visuals
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### Training / Proof Visuals
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### Evidence Artifacts
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- Sample rewards run folder: https://huggingface.co/spaces/md896/sql-debug-env/tree/main/artifacts/runs/20260426-064318-sample-rewards-32eval
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- Earlier 32-eval pass folder: https://huggingface.co/spaces/md896/sql-debug-env/tree/main/artifacts/runs/20260426-060502-final-pass-32eval
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## Bias, Risks, and Limitations
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- SQL correctness can still degrade under unseen schemas/dialects.
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- Benchmark-style gains do not guarantee equivalent production reliability.
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- Model outputs should be reviewed before executing in sensitive environments.
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## Recommendations
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- Keep SQL execution sandboxed during evaluation.
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- Use schema introspection + error inspection loops.
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- Add reviewer/guardrail checks for risky query classes.
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- Track run artifacts and compare against deterministic graders, not only manual inspection.
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## How to Get Started
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_id = "md896/sql-debug-agent-qwen25-05b-grpo-wandb-continue-v2"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id)
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prompt = "Fix this SQL query based on schema and error context: SELECT * FROM userss;"
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(**inputs, max_new_tokens=128)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## Environmental Impact
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This model was trained/evaluated across iterative cloud/local workflows. Exact carbon accounting is not yet logged in this card.
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## Citation
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If you use this work, cite the project repository and model page:
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- Repo: https://github.com/mdayan8/sql-debug-env
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- Model: https://huggingface.co/md896/sql-debug-agent-qwen25-05b-grpo-wandb-continue-v2
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## Contact
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- GitHub: https://github.com/mdayan8
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config.json
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size 988097824
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special_tokens_map.json
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||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151647": {
|
||||||
|
"content": "<|object_ref_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151648": {
|
||||||
|
"content": "<|box_start|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151649": {
|
||||||
|
"content": "<|box_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151650": {
|
||||||
|
"content": "<|quad_start|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151651": {
|
||||||
|
"content": "<|quad_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151652": {
|
||||||
|
"content": "<|vision_start|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151653": {
|
||||||
|
"content": "<|vision_end|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151654": {
|
||||||
|
"content": "<|vision_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151655": {
|
||||||
|
"content": "<|image_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151656": {
|
||||||
|
"content": "<|video_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": true
|
||||||
|
},
|
||||||
|
"151657": {
|
||||||
|
"content": "<tool_call>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151658": {
|
||||||
|
"content": "</tool_call>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151659": {
|
||||||
|
"content": "<|fim_prefix|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151660": {
|
||||||
|
"content": "<|fim_middle|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151661": {
|
||||||
|
"content": "<|fim_suffix|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151662": {
|
||||||
|
"content": "<|fim_pad|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151663": {
|
||||||
|
"content": "<|repo_name|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
},
|
||||||
|
"151664": {
|
||||||
|
"content": "<|file_sep|>",
|
||||||
|
"lstrip": false,
|
||||||
|
"normalized": false,
|
||||||
|
"rstrip": false,
|
||||||
|
"single_word": false,
|
||||||
|
"special": false
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"additional_special_tokens": [
|
||||||
|
"<|im_start|>",
|
||||||
|
"<|im_end|>",
|
||||||
|
"<|object_ref_start|>",
|
||||||
|
"<|object_ref_end|>",
|
||||||
|
"<|box_start|>",
|
||||||
|
"<|box_end|>",
|
||||||
|
"<|quad_start|>",
|
||||||
|
"<|quad_end|>",
|
||||||
|
"<|vision_start|>",
|
||||||
|
"<|vision_end|>",
|
||||||
|
"<|vision_pad|>",
|
||||||
|
"<|image_pad|>",
|
||||||
|
"<|video_pad|>"
|
||||||
|
],
|
||||||
|
"bos_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 Qwen, created by Alibaba Cloud. 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 Qwen, created by Alibaba Cloud. You 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",
|
||||||
|
"clean_up_tokenization_spaces": false,
|
||||||
|
"eos_token": "<|im_end|>",
|
||||||
|
"errors": "replace",
|
||||||
|
"extra_special_tokens": {},
|
||||||
|
"model_max_length": 131072,
|
||||||
|
"pad_token": "<|im_end|>",
|
||||||
|
"split_special_tokens": false,
|
||||||
|
"tokenizer_class": "Qwen2Tokenizer",
|
||||||
|
"unk_token": null
|
||||||
|
}
|
||||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user