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mrsandip
/
Alfa-Code

Text Generation
Transformers
Safetensors
GGUF
English
code
code-generation
multimodal
llama
Model card Files Files and versions
xet
Community

Instructions to use mrsandip/Alfa-Code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use mrsandip/Alfa-Code with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="mrsandip/Alfa-Code")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("mrsandip/Alfa-Code", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use mrsandip/Alfa-Code with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "mrsandip/Alfa-Code"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "mrsandip/Alfa-Code",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/mrsandip/Alfa-Code
  • SGLang

    How to use mrsandip/Alfa-Code 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 "mrsandip/Alfa-Code" \
        --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": "mrsandip/Alfa-Code",
    		"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 "mrsandip/Alfa-Code" \
            --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": "mrsandip/Alfa-Code",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use mrsandip/Alfa-Code with Docker Model Runner:

    docker model run hf.co/mrsandip/Alfa-Code

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Preview of files found in this repository
  • app
    Set data: grounded chat with retrieval 4 days ago
  • configs
    Add best 4GB scratch config 4 days ago
  • data
    Update Alfa-Code pipeline: HF datasets + Hub connect 4 days ago
  • notebooks
    Fix 401: add HF_TOKEN login cell 4 days ago
  • outputs
    Upload folder using huggingface_hub 1 day ago
  • scripts
    Train seq128 + adafactor + cpu flag 4 days ago
  • tokenizers
    Apply v0.2.0-best tokenizer to main 4 days ago
  • .env.example
    128 Bytes
    Update Alfa-Code pipeline: HF datasets + Hub connect 4 days ago
  • .gitattributes
    1.52 kB
    initial commit 4 days ago
  • .gitignore
    67 Bytes
    Update Alfa-Code pipeline: HF datasets + Hub connect 4 days ago
  • README.md
    1.14 kB
    Version 0.4.0-trained: loss 9.4 to 3.8 4 days ago
  • alfa.ipynb
    2.15 kB
    Fix 401: add HF_TOKEN login cell 4 days ago
  • requirements.txt
    180 Bytes
    Make all: data+tiny-50M+gguf-scripts+gradio-UI 4 days ago