Instructions to use notstoic/OPT-13B-Nerybus-Mix-4bit-128g with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use notstoic/OPT-13B-Nerybus-Mix-4bit-128g with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="notstoic/OPT-13B-Nerybus-Mix-4bit-128g")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("notstoic/OPT-13B-Nerybus-Mix-4bit-128g") model = AutoModelForCausalLM.from_pretrained("notstoic/OPT-13B-Nerybus-Mix-4bit-128g") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use notstoic/OPT-13B-Nerybus-Mix-4bit-128g with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "notstoic/OPT-13B-Nerybus-Mix-4bit-128g" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "notstoic/OPT-13B-Nerybus-Mix-4bit-128g", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/notstoic/OPT-13B-Nerybus-Mix-4bit-128g
- SGLang
How to use notstoic/OPT-13B-Nerybus-Mix-4bit-128g 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 "notstoic/OPT-13B-Nerybus-Mix-4bit-128g" \ --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": "notstoic/OPT-13B-Nerybus-Mix-4bit-128g", "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 "notstoic/OPT-13B-Nerybus-Mix-4bit-128g" \ --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": "notstoic/OPT-13B-Nerybus-Mix-4bit-128g", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use notstoic/OPT-13B-Nerybus-Mix-4bit-128g with Docker Model Runner:
docker model run hf.co/notstoic/OPT-13B-Nerybus-Mix-4bit-128g
- Xet hash:
- 79379d83aa24b9cac3436a6cd10cb2d39818ebc3fedba215d6009fd1c5a52453
- Size of remote file:
- 7.79 GB
- SHA256:
- 5ceb54eb4981e47f7a80d5cacb7686b31320ed640fe966eeb726a7a8eaf602c6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.