Instructions to use princeton-nlp/Sheared-LLaMA-1.3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use princeton-nlp/Sheared-LLaMA-1.3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="princeton-nlp/Sheared-LLaMA-1.3B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("princeton-nlp/Sheared-LLaMA-1.3B") model = AutoModelForCausalLM.from_pretrained("princeton-nlp/Sheared-LLaMA-1.3B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use princeton-nlp/Sheared-LLaMA-1.3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "princeton-nlp/Sheared-LLaMA-1.3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "princeton-nlp/Sheared-LLaMA-1.3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/princeton-nlp/Sheared-LLaMA-1.3B
- SGLang
How to use princeton-nlp/Sheared-LLaMA-1.3B 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 "princeton-nlp/Sheared-LLaMA-1.3B" \ --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": "princeton-nlp/Sheared-LLaMA-1.3B", "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 "princeton-nlp/Sheared-LLaMA-1.3B" \ --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": "princeton-nlp/Sheared-LLaMA-1.3B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use princeton-nlp/Sheared-LLaMA-1.3B with Docker Model Runner:
docker model run hf.co/princeton-nlp/Sheared-LLaMA-1.3B
include sample code to run the model in readme
#14 opened almost 2 years ago
by
oddlyspaced
Can provide a use sample?
1
#13 opened almost 2 years ago
by
wenine
Adding `safetensors` variant of this model
1
#12 opened about 2 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#11 opened over 2 years ago
by
SFconvertbot
Loss without grad_fn when using transformers Trainer suite
1
#10 opened over 2 years ago
by
syboomsysy
Adding `safetensors` variant of this model
👍 1
#9 opened over 2 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#8 opened over 2 years ago
by
SFconvertbot
Adding `safetensors` variant of this model
#7 opened over 2 years ago
by
SFconvertbot
Instruct version
2
#5 opened over 2 years ago
by
kimihailv
Great work + Excellent model
❤️ 2
1
#3 opened over 2 years ago
by
doberst
Congratulations on this!!!!!
❤️👍 8
#2 opened over 2 years ago
by
appvoid