Instructions to use openlm-research/open_llama_3b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openlm-research/open_llama_3b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="openlm-research/open_llama_3b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("openlm-research/open_llama_3b") model = AutoModelForCausalLM.from_pretrained("openlm-research/open_llama_3b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use openlm-research/open_llama_3b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "openlm-research/open_llama_3b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "openlm-research/open_llama_3b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/openlm-research/open_llama_3b
- SGLang
How to use openlm-research/open_llama_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 "openlm-research/open_llama_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": "openlm-research/open_llama_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 "openlm-research/open_llama_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": "openlm-research/open_llama_3b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use openlm-research/open_llama_3b with Docker Model Runner:
docker model run hf.co/openlm-research/open_llama_3b
Adding `safetensors` variant of this model
#15 opened about 1 year ago
by
SFconvertbot
Interview request: genAI evaluation & documentation
#14 opened over 1 year ago
by
evatang
Tokenizer of this version is not compatible with the original.
#13 opened almost 2 years ago
by
suhcrates
Adding Evaluation Results
#12 opened over 2 years ago
by
leaderboard-pr-bot
How to run on colab ?
1
#11 opened almost 3 years ago
by
deepakkaura26
Adding `safetensors` variant of this model
#10 opened almost 3 years ago
by
Z3R6X
zanezhang
#9 opened almost 3 years ago
by
zanezhang1
Is this commercially usable?
1
#7 opened almost 3 years ago
by
AayushShah
Adding `safetensors` variant of this model
👍 1
#6 opened almost 3 years ago
by
SFconvertbot
What is ddboolq in the evaluation? We cannot find the "ddboolq" task in lm-evaluation-harness.
1
#5 opened almost 3 years ago
by
CobraMamba
Adding `safetensors` variant of this model
#4 opened almost 3 years ago
by
SFconvertbot
Difference to RedPajama-INCITE-3B base model
#3 opened almost 3 years ago
by
Fredithefish
Enable LlamaTokenizerFast and AutoTokenizer to load in seconds rather than 5 minutes.
👍 1
1
#2 opened almost 3 years ago
by
danielhanchen
Adding `safetensors` variant of this model
#1 opened almost 3 years ago
by
SFconvertbot