Text Generation
Transformers
Safetensors
PyTorch
English
llama
facebook
meta
llama-3
Eval Results
text-generation-inference
Instructions to use meta-llama/Meta-Llama-3-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use meta-llama/Meta-Llama-3-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="meta-llama/Meta-Llama-3-8B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B") model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use meta-llama/Meta-Llama-3-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "meta-llama/Meta-Llama-3-8B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "meta-llama/Meta-Llama-3-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/meta-llama/Meta-Llama-3-8B
- SGLang
How to use meta-llama/Meta-Llama-3-8B 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 "meta-llama/Meta-Llama-3-8B" \ --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": "meta-llama/Meta-Llama-3-8B", "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 "meta-llama/Meta-Llama-3-8B" \ --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": "meta-llama/Meta-Llama-3-8B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use meta-llama/Meta-Llama-3-8B with Docker Model Runner:
docker model run hf.co/meta-llama/Meta-Llama-3-8B
中国区的账号, 都会被拒绝?
#124
by HLearning - opened
who can help me?
same +1
the same
why?
"Your request to access this repo has been rejected by the repo's authors." Why??
The same refused.
Feel free to clone from my repos guys
+1
HLearning changed discussion status to closed
Don't pretend it's open. Region-based restriction contradict the spirit of open-source. Please clarify it.
还装开源呢,搞起歧视来一套一套的,演的不演了,纯纯恶心人
+1
meta, totally bullshit
shame on meta!
shame on meta!!!!!!!!!!!!!!!!!!!!
骑着meta老冯子高调路过
扎卡波哥屁眼被我捅烂了