Text Generation
Transformers
TensorBoard
Safetensors
Chinese
English
code
qwen
lora
repository-understanding
code-assistant
fine-tuning
multi-agent-systems
Eval Results (legacy)
Instructions to use tensense/code_repo_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensense/code_repo_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="tensense/code_repo_finetuning")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tensense/code_repo_finetuning", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use tensense/code_repo_finetuning with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tensense/code_repo_finetuning" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tensense/code_repo_finetuning", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/tensense/code_repo_finetuning
- SGLang
How to use tensense/code_repo_finetuning with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "tensense/code_repo_finetuning" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tensense/code_repo_finetuning", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "tensense/code_repo_finetuning" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tensense/code_repo_finetuning", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use tensense/code_repo_finetuning with Docker Model Runner:
docker model run hf.co/tensense/code_repo_finetuning
File size: 3,507 Bytes
4e909c7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 | # Laddr - Complete Requirements # This file includes all dependencies for the laddr framework, # including documentation, development, and optional integrations. # ============================================================================ # Laddr Package & Build Tools # ============================================================================ laddr>=0.8.1 build twine # ============================================================================ # Core Runtime Dependencies # ============================================================================ pydantic>=2.11.9 pydantic-settings>=2.10.1 requests>=2.31.0 python-dotenv>=1.1.1 # FastAPI and Web fastapi>=0.115.0 uvicorn[standard]>=0.32.0 # Message Queue redis>=5.0.0 # Database sqlalchemy>=2.0.0 psycopg2-binary>=2.9.0 # CLI click>=8.1.7 rich>=13.7.0 pyyaml>=6.0.1 jinja2>=3.1.0 # ============================================================================ # LLM Providers # ============================================================================ openai>=1.13.3 litellm google-generativeai>=0.8.0 # anthropic>=0.34.0 # groq>=0.11.0 # ============================================================================ # Documentation Dependencies # ============================================================================ mkdocs>=1.6.1 mkdocs-material>=9.5.0 mkdocstrings>=0.26.0 mkdocstrings-python>=1.0.0 mkdocs-autorefs>=1.2.0 mkdocs-click>=0.8.0 # ============================================================================ # Development Dependencies # ============================================================================ # Testing pytest>=8.0.0 pytest-asyncio>=0.23.0 pytest-subprocess>=1.5.3 pytest-recording>=0.13.4 pytest-randomly>=4.0.1 pytest-timeout>=2.4.0 pytest-xdist>=3.8.0 pytest-split>=0.10.0 vcrpy==7.0.0 # Code Quality black>=24.0.0 ruff>=0.5.0 mypy>=1.11.0 pre-commit>=4.3.0 bandit>=1.8.6 # Type Stubs types-requests>=2.31.0 types-pyyaml>=6.0.0 types-regex>=2024.11.6 types-appdirs>=1.4.0 types-psycopg2>=2.9.21 types-pymysql>=1.1.0 boto3-stubs[bedrock-runtime]>=1.40.54 # ============================================================================ # Optional Database Dependencies (uncomment as needed) # ============================================================================ # pymysql>=1.1.0 # MySQL # ============================================================================ # Optional Storage Dependencies (uncomment as needed) # ============================================================================ # boto3>=1.34.0 # AWS S3 # minio>=7.2.0 # MinIO # ============================================================================ # Optional Message Queue Dependencies (uncomment as needed) # ============================================================================ # aiokafka>=0.11.0 # Apache Kafka # aio-pika>=9.4.0 # RabbitMQ # ============================================================================ # Installation Instructions # ============================================================================ # For core installation only: # pip install -r requirements.txt --only-binary :all: # # For development (includes testing and linting): # pip install -r requirements.txt # # For documentation (includes mkdocs): # pip install -r requirements.txt # # To install laddr package in editable mode: # pip install -e lib/laddr # # To install with all optional dependencies: # Uncomment the optional sections above and run: docker>=7.0.0 |