Text Generation
Transformers
PyTorch
Safetensors
English
llama
llama-2
self-instruct
distillation
synthetic instruction
text-generation-inference
Instructions to use NousResearch/Nous-Hermes-Llama2-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NousResearch/Nous-Hermes-Llama2-13b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="NousResearch/Nous-Hermes-Llama2-13b")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("NousResearch/Nous-Hermes-Llama2-13b") model = AutoModelForMultimodalLM.from_pretrained("NousResearch/Nous-Hermes-Llama2-13b") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use NousResearch/Nous-Hermes-Llama2-13b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NousResearch/Nous-Hermes-Llama2-13b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NousResearch/Nous-Hermes-Llama2-13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/NousResearch/Nous-Hermes-Llama2-13b
- SGLang
How to use NousResearch/Nous-Hermes-Llama2-13b 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 "NousResearch/Nous-Hermes-Llama2-13b" \ --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": "NousResearch/Nous-Hermes-Llama2-13b", "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 "NousResearch/Nous-Hermes-Llama2-13b" \ --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": "NousResearch/Nous-Hermes-Llama2-13b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use NousResearch/Nous-Hermes-Llama2-13b with Docker Model Runner:
docker model run hf.co/NousResearch/Nous-Hermes-Llama2-13b
support for Ollama
1
#17 opened over 1 year ago
by
mineworkshare
code of big-bench evaluation
1
#15 opened about 2 years ago
by
danigambit
What's the price for this model?
1
#13 opened over 2 years ago
by
Yvaine0508
Adding Evaluation Results
#11 opened over 2 years ago
by
leaderboard-pr-bot
Merging the .bin files
2
#10 opened over 2 years ago
by
Lue-C
Failed to run in AWS SageMaker
4
#9 opened almost 3 years ago
by
fangleen
Max context tokens
1
#7 opened almost 3 years ago
by
jacksee
Whats coding datasets were used?
👍 2
4
#3 opened almost 3 years ago
by
rombodawg