Instructions to use openlm-research/open_llama_13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openlm-research/open_llama_13b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="openlm-research/open_llama_13b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("openlm-research/open_llama_13b") model = AutoModelForCausalLM.from_pretrained("openlm-research/open_llama_13b") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use openlm-research/open_llama_13b 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_13b" # 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_13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/openlm-research/open_llama_13b
- SGLang
How to use openlm-research/open_llama_13b 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_13b" \ --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_13b", "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_13b" \ --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_13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use openlm-research/open_llama_13b with Docker Model Runner:
docker model run hf.co/openlm-research/open_llama_13b
13B Transformers instantiation: Error no file named pytorch_model.bin, model.safetensors, tf_model.h5, model.ckpt.index or flax_model.msgpack found in directory
#12 opened over 1 year ago
by
devonoved
Adding `safetensors` variant of this model
#11 opened about 2 years ago
by
SFconvertbot
Adding Evaluation Results
#10 opened over 2 years ago
by
leaderboard-pr-bot
Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu!
1
#9 opened almost 3 years ago
by
smshr
question answering using llama
1
#7 opened almost 3 years ago
by
Iamexperimenting
Adding `safetensors` variant of this model
#6 opened almost 3 years ago
by
eyang9002
tied weights
2
#5 opened almost 3 years ago
by
shiyu-wangbyte
I got an error while initializing the model
#4 opened almost 3 years ago
by
hamza007
Prompt format?
1
#3 opened almost 3 years ago
by
iamrobotbear
Multilinguality
👍 4
3
#2 opened almost 3 years ago
by
avacaondata
Delta weights
2
#1 opened almost 3 years ago
by
Asaf-Yehudai