68 lines
1.6 KiB
Markdown
68 lines
1.6 KiB
Markdown
# SIA Training Tool
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This tool provides command-line utilities for fine-tuning SIA's language models.
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## Supported Models
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- DeepSeek R1 models (including distilled versions)
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- Mistral models
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## Commands
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### train_deepseek
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Fine-tune DeepSeek models using Unsloth optimization.
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```bash
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train_deepseek --base-model deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B --output-dir /root/models/DeepSeek-R1-Distill-Qwen-1.5B
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```
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Options:
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- `--config`: Path to training configuration file (default: /root/sia/training/config.yaml)
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- `--base-model`: HuggingFace model ID for the base model (required)
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- `--output-dir`: Directory to save model (required)
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- `--api-key`: HuggingFace API key (optional, will use SIA_HF_API_KEY)
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### train_mistral
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Fine-tune Mistral models using Mistral's API.
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```bash
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train_mistral --model mistral-large-latest
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```
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Options:
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- `--config`: Path to training configuration file (default: /root/sia/training/config.yaml)
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- `--model`: Base model name (default: mistral-large-latest)
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- `--api-key`: Mistral API key (optional, will use SIA_MISTRAL_API_KEY)
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## Configuration Format
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The training configuration file (YAML) should include:
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```yaml
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model:
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system_prompt_path: "/root/sia/system_prompt.md"
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action_schema: "/root/sia/action_schema.xsd"
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params:
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learning_rate: 1e-5
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epochs: 3
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data:
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- "/root/sia/training/data_dir1/"
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- "/root/sia/training/data_dir2/"
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```
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## Data Format
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Training data should be XML files in the following format:
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```xml
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<iteration system_prompt_hash="..." action_schema_hash="...">
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<context>
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<!-- XML context -->
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</context>
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<response>
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<!-- Model response -->
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</response>
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</iteration>
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``` |