test 1 stop #7
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| name: Create HuggingFace Model Repository | |
| # on: | |
| # workflow_dispatch: | |
| # inputs: | |
| # model_name: | |
| # description: "Name of the model to create (will be used in repo name and files)" | |
| # required: true | |
| # type: string | |
| # prompt_template: | |
| # description: "Prompt template for the model" | |
| # required: true | |
| # type: string | |
| # stop_tokens: | |
| # description: "Stop tokens for the model (comma-separated)" | |
| # required: true | |
| # type: string | |
| # engine: | |
| # description: "Engine to run the model (e.g., llama-cpp)" | |
| # required: true | |
| # type: string | |
| # env: | |
| # USER_NAME: cortexso | |
| # MODEL_NAME: ${{ inputs.model_name }} | |
| on: | |
| push: | |
| branches: | |
| - add/create_modelyml_workflow | |
| env: | |
| USER_NAME: cortexso | |
| MODEL_NAME: "test-model" # Default test value | |
| PROMPT_TEMPLATE: "<|im_start|>system\n{system_message}<|im_end|>\n<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant" # Default test value | |
| STOP_TOKENS: "<|im_end|>" # Default test value | |
| ENGINE: "llama-cpp" # Default test value | |
| jobs: | |
| create-repo: | |
| runs-on: ubuntu-20-04-gguf | |
| timeout-minutes: 7200 | |
| steps: | |
| - name: Checkout | |
| uses: actions/checkout@v4 | |
| - name: Set up Python | |
| uses: actions/setup-python@v5 | |
| with: | |
| python-version: '3.10' | |
| - name: Cache Python packages | |
| uses: actions/cache@v4 | |
| with: | |
| path: | | |
| ~/.cache/pip | |
| ~/.local/share/pip | |
| .venv | |
| key: ${{ runner.os }}-pip-${{ github.sha }} | |
| restore-keys: | | |
| ${{ runner.os }}-pip- | |
| - name: Install dependencies | |
| run: | | |
| pip install huggingface_hub PyYAML | |
| git lfs install | |
| - name: Create YAML files | |
| run: | | |
| python3 - << EOF | |
| import yaml | |
| import os | |
| # Function to create a custom string representer | |
| def quoted_presenter(dumper, data): | |
| return dumper.represent_scalar('tag:yaml.org,2002:str', data, style='"') | |
| # Register the custom presenter | |
| yaml.add_representer(str, quoted_presenter) | |
| # Process stop tokens | |
| stop_tokens = os.environ['STOP_TOKENS'].split(',') | |
| stop_tokens = [token.strip() for token in stop_tokens if token.strip()] | |
| # Create model.yml content | |
| model_content = { | |
| 'id': os.environ['MODEL_NAME'], | |
| 'model': os.environ['MODEL_NAME'], | |
| 'name': os.environ['MODEL_NAME'], | |
| 'version': 1, | |
| 'stop': stop_tokens, | |
| 'stream': True, | |
| 'top_p': 0.9, | |
| 'temperature': 0.7, | |
| 'frequency_penalty': 0, | |
| 'presence_penalty': 0, | |
| 'max_tokens': 4096, | |
| 'seed': -1, | |
| 'dynatemp_range': 0, | |
| 'dynatemp_exponent': 1, | |
| 'top_k': 40, | |
| 'min_p': 0.05, | |
| 'tfs_z': 1, | |
| 'typ_p': 1, | |
| 'repeat_last_n': 64, | |
| 'repeat_penalty': 1, | |
| 'mirostat': False, | |
| 'mirostat_tau': 5, | |
| 'mirostat_eta': 0.100000001, | |
| 'penalize_nl': False, | |
| 'ignore_eos': False, | |
| 'n_probs': 0, | |
| 'min_keep': 0, | |
| 'engine': os.environ['ENGINE'], | |
| 'prompt_template': os.environ['PROMPT_TEMPLATE'], | |
| 'ctx_len': 4096, | |
| 'ngl': 34 | |
| } | |
| # Create the model.yml file with proper sections and comments | |
| with open('model.yml', 'w') as f: | |
| f.write("# BEGIN GENERAL GGUF METADATA\n") | |
| yaml.dump({k: model_content[k] for k in ['id', 'model', 'name', 'version']}, | |
| f, default_flow_style=False, sort_keys=False) | |
| f.write("\n# END GENERAL GGUF METADATA\n\n") | |
| f.write("# BEGIN INFERENCE PARAMETERS\n# BEGIN REQUIRED\n") | |
| yaml.dump({'stop': model_content['stop']}, f, default_flow_style=False) | |
| f.write("# END REQUIRED\n\n") | |
| f.write("# BEGIN OPTIONAL\n") | |
| optional_params = dict((k, model_content[k]) for k in [ | |
| 'stream', 'top_p', 'temperature', 'frequency_penalty', | |
| 'presence_penalty', 'max_tokens', 'seed', 'dynatemp_range', | |
| 'dynatemp_exponent', 'top_k', 'min_p', 'tfs_z', 'typ_p', | |
| 'repeat_last_n', 'repeat_penalty', 'mirostat', 'mirostat_tau', | |
| 'mirostat_eta', 'penalize_nl', 'ignore_eos', 'n_probs', 'min_keep' | |
| ]) | |
| yaml.dump(optional_params, f, default_flow_style=False) | |
| f.write("# END OPTIONAL\n") | |
| f.write("# END INFERENCE PARAMETERS\n\n") | |
| f.write("# BEGIN MODEL LOAD PARAMETERS\n# BEGIN REQUIRED\n") | |
| required_params = dict((k, model_content[k]) for k in [ | |
| 'engine', 'prompt_template', 'ctx_len', 'ngl' | |
| ]) | |
| yaml.dump(required_params, f, default_flow_style=False) | |
| f.write("# END OPTIONAL\n") | |
| f.write("# END MODEL LOAD PARAMETERS\n") | |
| # Create metadata.yml content | |
| metadata_content = { | |
| 'version': 1, | |
| 'name': os.environ['MODEL_NAME'], | |
| 'default': '8b-gguf-q4-km' | |
| } | |
| with open('metadata.yml', 'w') as f: | |
| yaml.dump(metadata_content, f, default_flow_style=False) | |
| EOF | |
| - name: Create HuggingFace Repository and Upload Files | |
| env: | |
| HF_TOKEN: ${{ secrets.HUGGINGFACE_TOKEN_WRITE }} | |
| run: | | |
| python3 - << EOF | |
| from huggingface_hub import HfApi, create_repo | |
| import os | |
| # Initialize the Hugging Face API | |
| api = HfApi(token=os.environ['HF_TOKEN']) | |
| # Create the repository | |
| repo_id = f"${{ env.USER_NAME }}/${{ env.MODEL_NAME }}" | |
| try: | |
| create_repo(repo_id, private=False, token=os.environ['HF_TOKEN']) | |
| print(f"Created repository: {repo_id}") | |
| except Exception as e: | |
| print(f"Repository might already exist or error occurred: {e}") | |
| # Upload the files | |
| api.upload_file( | |
| path_or_fileobj="model.yml", | |
| path_in_repo="model.yml", | |
| repo_id=repo_id, | |
| token=os.environ['HF_TOKEN'] | |
| ) | |
| api.upload_file( | |
| path_or_fileobj="metadata.yml", | |
| path_in_repo="metadata.yml", | |
| repo_id=repo_id, | |
| token=os.environ['HF_TOKEN'] | |
| ) | |
| print("Files uploaded successfully") | |
| EOF | |
| - name: Cleanup | |
| run: | | |
| rm -f model.yml metadata.yml |