Text Generation
Transformers
PyTorch
TensorFlow
JAX
LiteRT
Rust
ONNX
Safetensors
English
gpt2
exbert
text-generation-inference
Instructions to use openai-community/gpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openai-community/gpt2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="openai-community/gpt2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2") model = AutoModelForCausalLM.from_pretrained("openai-community/gpt2") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use openai-community/gpt2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openai-community/gpt2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openai-community/gpt2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/openai-community/gpt2
- SGLang
How to use openai-community/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 "openai-community/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": "openai-community/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 "openai-community/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": "openai-community/gpt2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use openai-community/gpt2 with Docker Model Runner:
docker model run hf.co/openai-community/gpt2
Commit ·
f27b190
1
Parent(s): 0dd7bcc
Add note that this is the smallest version of the model (#18)
Browse files- Add note that this is the smallest version of the model (611838ef095a5bb35bf2027d05e1194b7c9d37ac)
Co-authored-by: helen <mathemakitten@users.noreply.huggingface.co>
README.md
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@@ -34,6 +34,10 @@ This way, the model learns an inner representation of the English language that
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useful for downstream tasks. The model is best at what it was pretrained for however, which is generating texts from a
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prompt.
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## Intended uses & limitations
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You can use the raw model for text generation or fine-tune it to a downstream task. See the
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useful for downstream tasks. The model is best at what it was pretrained for however, which is generating texts from a
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prompt.
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This is the **smallest** version of GPT-2, with 124M parameters.
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**Related Models:** [GPT-Large](https://huggingface.co/gpt2-large), [GPT-Medium](https://huggingface.co/gpt2-medium) and [GPT-XL](https://huggingface.co/gpt2-xl)
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## Intended uses & limitations
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You can use the raw model for text generation or fine-tune it to a downstream task. See the
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