Instructions to use ypwhere/LQK-BabyLM-Strict with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ypwhere/LQK-BabyLM-Strict with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ypwhere/LQK-BabyLM-Strict", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ypwhere/LQK-BabyLM-Strict", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ypwhere/LQK-BabyLM-Strict with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ypwhere/LQK-BabyLM-Strict" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ypwhere/LQK-BabyLM-Strict", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ypwhere/LQK-BabyLM-Strict
- SGLang
How to use ypwhere/LQK-BabyLM-Strict 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 "ypwhere/LQK-BabyLM-Strict" \ --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": "ypwhere/LQK-BabyLM-Strict", "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 "ypwhere/LQK-BabyLM-Strict" \ --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": "ypwhere/LQK-BabyLM-Strict", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ypwhere/LQK-BabyLM-Strict with Docker Model Runner:
docker model run hf.co/ypwhere/LQK-BabyLM-Strict
| { | |
| "filename": "ckpt_final-w0910M-i004797.pt", | |
| "sha256": "dfaff6e50e0759fed5469af2022205228068aa12354537de22ebcde769b32995", | |
| "role": "final", | |
| "iter_num": 4797, | |
| "num_updates": 4797, | |
| "tokens_seen": 1257504768, | |
| "words_seen": 910196864, | |
| "labels": [ | |
| { | |
| "series": "words", | |
| "name": "words_final", | |
| "revision": "chck_910M", | |
| "target": 910196864, | |
| "actual": 910196864 | |
| }, | |
| { | |
| "series": "tokens", | |
| "name": "tokens_final", | |
| "revision": "chck_1258M", | |
| "target": 1257504768, | |
| "actual": 1257504768 | |
| } | |
| ], | |
| "git_sha": "71b982e505ea3f804c54a4b4c0834bd1eee54da8" | |
| } | |