Text Generation
Transformers
PyTorch
English
gpt2
language-model
transformer
tiny-shakespeare
text-generation-inference
Instructions to use Pavloria/mini-language-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Pavloria/mini-language-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Pavloria/mini-language-model")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Pavloria/mini-language-model") model = AutoModel.from_pretrained("Pavloria/mini-language-model") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Pavloria/mini-language-model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Pavloria/mini-language-model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Pavloria/mini-language-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Pavloria/mini-language-model
- SGLang
How to use Pavloria/mini-language-model 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 "Pavloria/mini-language-model" \ --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": "Pavloria/mini-language-model", "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 "Pavloria/mini-language-model" \ --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": "Pavloria/mini-language-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Pavloria/mini-language-model with Docker Model Runner:
docker model run hf.co/Pavloria/mini-language-model
Upload README.md with huggingface_hub
Browse files
README.md
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# Mini Language Model
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This is a toy decoder-only model trained on Tiny Shakespeare.
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---
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language: en
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license: mit
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tags:
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- pytorch
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- language-model
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- transformer
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- tiny-shakespeare
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library_name: transformers
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model_name: mini-language-model
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pipeline_tag: text-generation
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---
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# Mini Language Model
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This is a toy decoder-only model trained on Tiny Shakespeare.
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