Hugging Face's logo Hugging Face
  • Models
  • Datasets
  • Spaces
  • Buckets new
  • Docs
  • Enterprise
  • Pricing

  • Log In
  • Sign Up

replit
/
replit-code-v1-3b

Text Generation
Transformers
PyTorch
code
mpt
custom_code
Eval Results (legacy)
text-generation-inference
Model card Files Files and versions
xet
Community
38

Instructions to use replit/replit-code-v1-3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use replit/replit-code-v1-3b with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="replit/replit-code-v1-3b", trust_remote_code=True)
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("replit/replit-code-v1-3b", trust_remote_code=True)
    model = AutoModelForCausalLM.from_pretrained("replit/replit-code-v1-3b", trust_remote_code=True)
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use replit/replit-code-v1-3b with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "replit/replit-code-v1-3b"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "replit/replit-code-v1-3b",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/replit/replit-code-v1-3b
  • SGLang

    How to use replit/replit-code-v1-3b 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 "replit/replit-code-v1-3b" \
        --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": "replit/replit-code-v1-3b",
    		"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 "replit/replit-code-v1-3b" \
            --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": "replit/replit-code-v1-3b",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use replit/replit-code-v1-3b with Docker Model Runner:

    docker model run hf.co/replit/replit-code-v1-3b
replit-code-v1-3b
819 kB
Ctrl+K
Ctrl+K
  • 4 contributors
History: 32 commits
Alim111's picture
Alim111
Delete pytorch_model.bin
2dcb455 verified 3 months ago
  • .gitattributes
    1.48 kB
    initial commit about 3 years ago
  • README.md
    8.76 kB
    Fix typos in README (#28) almost 3 years ago
  • adapt_tokenizer.py
    1.75 kB
    Convert ReplitLM to MPT (#16) almost 3 years ago
  • attention.py
    16.2 kB
    Convert ReplitLM to MPT (#16) almost 3 years ago
  • blocks.py
    2.53 kB
    Convert ReplitLM to MPT (#16) almost 3 years ago
  • config.json
    1.25 kB
    Add eos_token_id to config (#26) almost 3 years ago
  • configuration_mpt.py
    9.2 kB
    Convert ReplitLM to MPT (#16) almost 3 years ago
  • generation_config.json
    112 Bytes
    Update generation_config.json (#25) almost 3 years ago
  • hf_prefixlm_converter.py
    27.2 kB
    Convert ReplitLM to MPT (#16) almost 3 years ago
  • meta_init_context.py
    3.64 kB
    Convert ReplitLM to MPT (#16) almost 3 years ago
  • modeling_mpt.py
    17.6 kB
    Update modeling_mpt.py (#19) almost 3 years ago
  • norm.py
    2.56 kB
    Convert ReplitLM to MPT (#16) almost 3 years ago
  • param_init_fns.py
    12.6 kB
    Convert ReplitLM to MPT (#16) almost 3 years ago
  • replit_lm_tokenizer.py
    6.26 kB
    Convert ReplitLM to MPT (#16) almost 3 years ago
  • special_tokens_map.json
    87 Bytes
    Convert ReplitLM to MPT (#16) almost 3 years ago
  • spiece.model
    708 kB
    xet
    Add files for release (#1) about 3 years ago
  • tokenizer_config.json
    400 Bytes
    Convert ReplitLM to MPT (#16) almost 3 years ago