Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing
    • Website
      • Tasks
      • HuggingChat
      • Collections
      • Languages
      • Organizations
    • Community
      • Blog
      • Posts
      • Daily Papers
      • Hardware
      • Learn
      • Discord
      • Forum
      • GitHub
    • Solutions
      • Team & Enterprise
      • Hugging Face PRO
      • Enterprise Support
      • Inference Providers
      • Inference Endpoints
      • Storage Buckets

  • Log In
  • Sign Up

EclipseNomad
/
Smart-Solidity-beta

Text Generation
Transformers
PyTorch
English
llama
code
blockchain
solidity
smart contract
text-generation-inference
Model card Files Files and versions
xet
Community

Instructions to use EclipseNomad/Smart-Solidity-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use EclipseNomad/Smart-Solidity-beta with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="EclipseNomad/Smart-Solidity-beta")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("EclipseNomad/Smart-Solidity-beta")
    model = AutoModelForCausalLM.from_pretrained("EclipseNomad/Smart-Solidity-beta", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use EclipseNomad/Smart-Solidity-beta with vLLM:

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

    How to use EclipseNomad/Smart-Solidity-beta 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 "EclipseNomad/Smart-Solidity-beta" \
        --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": "EclipseNomad/Smart-Solidity-beta",
    		"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 "EclipseNomad/Smart-Solidity-beta" \
            --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": "EclipseNomad/Smart-Solidity-beta",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use EclipseNomad/Smart-Solidity-beta with Docker Model Runner:

    docker model run hf.co/EclipseNomad/Smart-Solidity-beta

You need to agree to share your contact information to access this model

This repository is publicly accessible, but you have to accept the conditions to access its files and content.

Log in or Sign Up to review the conditions and access this model content.

Gated model
You can list files but not access them

Preview of files found in this repository
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    3.8 kB
    Update README.md over 1 year ago
  • config.json
    640 Bytes
    Added model weights and config files over 1 year ago
  • generation_config.json
    111 Bytes
    Added model weights and config files over 1 year ago
  • pytorch_model-00001-of-00002.bin
    9.98 GB
    xet
    Added model weights and config files over 1 year ago
  • pytorch_model-00002-of-00002.bin
    3.5 GB
    xet
    Added model weights and config files over 1 year ago
  • pytorch_model.bin.index.json
    24 kB
    Added model weights and config files over 1 year ago
  • special_tokens_map.json
    535 Bytes
    Added model weights and config files over 1 year ago
  • tokenizer.json
    1.84 MB
    Added model weights and config files over 1 year ago
  • tokenizer_config.json
    983 Bytes
    Added model weights and config files over 1 year ago