Text Generation
Transformers
Safetensors
PyTorch
tiny_shakespeare
causal-lm
shakespeare
educational
custom_code
Instructions to use aaronmac/tiny-shakespeare with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aaronmac/tiny-shakespeare with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aaronmac/tiny-shakespeare", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("aaronmac/tiny-shakespeare", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use aaronmac/tiny-shakespeare with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aaronmac/tiny-shakespeare" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aaronmac/tiny-shakespeare", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/aaronmac/tiny-shakespeare
- SGLang
How to use aaronmac/tiny-shakespeare 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 "aaronmac/tiny-shakespeare" \ --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": "aaronmac/tiny-shakespeare", "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 "aaronmac/tiny-shakespeare" \ --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": "aaronmac/tiny-shakespeare", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use aaronmac/tiny-shakespeare with Docker Model Runner:
docker model run hf.co/aaronmac/tiny-shakespeare
Download tokenizer.json from aaronmac/tiny-shakespeare: direct link, hf CLI and curl.
- Browser
- Download file 605 Bytes
-
https://huggingface.co/aaronmac/tiny-shakespeare/resolve/main/tokenizer.json
- Command line
-
hf download hf://aaronmac/tiny-shakespeare/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/aaronmac/tiny-shakespeare/resolve/main/tokenizer.json
605 Bytes
| { | |
| "chars": [ | |
| "\n", | |
| " ", | |
| "!", | |
| "$", | |
| "&", | |
| "'", | |
| ",", | |
| "-", | |
| ".", | |
| "3", | |
| ":", | |
| ";", | |
| "?", | |
| "A", | |
| "B", | |
| "C", | |
| "D", | |
| "E", | |
| "F", | |
| "G", | |
| "H", | |
| "I", | |
| "J", | |
| "K", | |
| "L", | |
| "M", | |
| "N", | |
| "O", | |
| "P", | |
| "Q", | |
| "R", | |
| "S", | |
| "T", | |
| "U", | |
| "V", | |
| "W", | |
| "X", | |
| "Y", | |
| "Z", | |
| "a", | |
| "b", | |
| "c", | |
| "d", | |
| "e", | |
| "f", | |
| "g", | |
| "h", | |
| "i", | |
| "j", | |
| "k", | |
| "l", | |
| "m", | |
| "n", | |
| "o", | |
| "p", | |
| "q", | |
| "r", | |
| "s", | |
| "t", | |
| "u", | |
| "v", | |
| "w", | |
| "x", | |
| "y", | |
| "z" | |
| ] | |
| } |