Instructions to use Maykeye/TinyLLama-v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maykeye/TinyLLama-v0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Maykeye/TinyLLama-v0")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Maykeye/TinyLLama-v0") model = AutoModelForCausalLM.from_pretrained("Maykeye/TinyLLama-v0") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Maykeye/TinyLLama-v0 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Maykeye/TinyLLama-v0" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Maykeye/TinyLLama-v0", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Maykeye/TinyLLama-v0
- SGLang
How to use Maykeye/TinyLLama-v0 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 "Maykeye/TinyLLama-v0" \ --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": "Maykeye/TinyLLama-v0", "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 "Maykeye/TinyLLama-v0" \ --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": "Maykeye/TinyLLama-v0", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Maykeye/TinyLLama-v0 with Docker Model Runner:
docker model run hf.co/Maykeye/TinyLLama-v0
| import shutil | |
| from pathlib import Path | |
| import time | |
| copied = [] | |
| while True: | |
| existing = [x.name for x in Path(".").glob("*.bin")] | |
| copy_from = [x for x in Path("/home/fella/mnt/selectel/tiny-llama/").glob("*.bin")] | |
| for file in copy_from: | |
| if file.name not in existing: | |
| print(file) | |
| try: | |
| shutil.copy(file, file.name) | |
| copied.append(file.name) | |
| if len(copied) > 6: | |
| delete_me = copied.pop(0) | |
| Path(delete_me).unlink() | |
| except Exception as e: | |
| print(f"Skipping {file.name}: {e}") | |
| pass | |
| time.sleep(15) | |