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

eu-test
/
gpt2

Text Generation
Transformers
PyTorch
google-tensorflow TensorFlow
JAX
LiteRT
Rust
ONNX
Safetensors
English
gpt2
exbert
text-generation-inference
🇪🇺 Region: EU
Model card Files Files and versions
xet
Community
1

Instructions to use eu-test/gpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use eu-test/gpt2 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="eu-test/gpt2")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("eu-test/gpt2")
    model = AutoModelForCausalLM.from_pretrained("eu-test/gpt2")
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps Settings
  • vLLM

    How to use eu-test/gpt2 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "eu-test/gpt2"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "eu-test/gpt2",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/eu-test/gpt2
  • SGLang

    How to use eu-test/gpt2 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 "eu-test/gpt2" \
        --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": "eu-test/gpt2",
    		"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 "eu-test/gpt2" \
            --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": "eu-test/gpt2",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use eu-test/gpt2 with Docker Model Runner:

    docker model run hf.co/eu-test/gpt2

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
  • onnx
    Adding ONNX file of this model (#60) about 3 years ago
  • .gitattributes
    445 Bytes
    Convert weights to .safetensors (#6) almost 4 years ago
  • 64-8bits.tflite
    125 MB
    xet
    Update 64-8bits.tflite over 6 years ago
  • 64-fp16.tflite
    248 MB
    xet
    Update 64-fp16.tflite over 6 years ago
  • 64.tflite
    496 MB
    xet
    Update 64.tflite over 6 years ago
  • README.md
    8.09 kB
    Add note that this is the smallest version of the model (#18) over 3 years ago
  • config.json
    665 Bytes
    Update config.json about 6 years ago
  • flax_model.msgpack
    498 MB
    xet
    add gpt2 about 5 years ago
  • generation_config.json
    124 Bytes
    Update generation_config.json over 3 years ago
  • merges.txt
    456 kB
    Update merges.txt over 7 years ago
  • model.safetensors
    548 MB
    xet
    Upload model.safetensors with huggingface_hub (#12) over 3 years ago
  • pytorch_model.bin
    548 MB
    xet
    Update pytorch_model.bin over 7 years ago
  • rust_model.ot
    703 MB
    xet
    Update rust_model.ot about 6 years ago
  • tf_model.h5
    498 MB
    xet
    Update tf_model.h5 almost 7 years ago
  • tokenizer.json
    1.36 MB
    Update tokenizer.json over 5 years ago
  • vocab.json
    1.04 MB
    Update vocab.json over 7 years ago