Text Generation
Transformers
PyTorch
TensorFlow
JAX
LiteRT
Rust
Core ML
Safetensors
English
gpt2
exbert
Eval Results (legacy)
text-generation-inference
Instructions to use distilbert/distilgpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distilbert/distilgpt2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="distilbert/distilgpt2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("distilbert/distilgpt2") model = AutoModelForCausalLM.from_pretrained("distilbert/distilgpt2") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use distilbert/distilgpt2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "distilbert/distilgpt2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "distilbert/distilgpt2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/distilbert/distilgpt2
- SGLang
How to use distilbert/distilgpt2 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 "distilbert/distilgpt2" \ --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": "distilbert/distilgpt2", "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 "distilbert/distilgpt2" \ --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": "distilbert/distilgpt2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use distilbert/distilgpt2 with Docker Model Runner:
docker model run hf.co/distilbert/distilgpt2
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language: en
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tags:
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- exbert
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license: apache-2.0
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datasets:
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- openwebtext
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model-index:
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- name: distilgpt2
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results:
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type: text-generation
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name: Text Generation
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dataset:
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type: wikitext
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name: WikiText-103
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metrics:
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co2_eq_emissions: 149200
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---
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# DistilGPT2
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<a href="https://huggingface.co/exbert/?model=distilgpt2">
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<img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png">
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</a>
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language: en
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tags:
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- exbert
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license: apache-2.0
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datasets:
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- openwebtext
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model-index:
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- name: distilgpt2
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results:
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type: text-generation
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name: Text Generation
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dataset:
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type: wikitext
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name: WikiText-103
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metrics:
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- type: perplexity
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name: Perplexity
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value: 21.1
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co2_eq_emissions: 149200
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base_model:
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- openai-community/gpt2
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---
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# DistilGPT2
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<a href="https://huggingface.co/exbert/?model=distilgpt2">
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<img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png">
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</a>
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