Instructions to use relaxml/Llama-2-70b-E8P-2Bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use relaxml/Llama-2-70b-E8P-2Bit with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="relaxml/Llama-2-70b-E8P-2Bit")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("relaxml/Llama-2-70b-E8P-2Bit")
model = AutoModelForCausalLM.from_pretrained("relaxml/Llama-2-70b-E8P-2Bit")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use relaxml/Llama-2-70b-E8P-2Bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "relaxml/Llama-2-70b-E8P-2Bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "relaxml/Llama-2-70b-E8P-2Bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/relaxml/Llama-2-70b-E8P-2Bit

SGLang

How to use relaxml/Llama-2-70b-E8P-2Bit 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 "relaxml/Llama-2-70b-E8P-2Bit" \
    --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": "relaxml/Llama-2-70b-E8P-2Bit",
		"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 "relaxml/Llama-2-70b-E8P-2Bit" \
        --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": "relaxml/Llama-2-70b-E8P-2Bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use relaxml/Llama-2-70b-E8P-2Bit with Docker Model Runner:
```
docker model run hf.co/relaxml/Llama-2-70b-E8P-2Bit
```

Llama-2-70b-E8P-2Bit

Commit History

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Commit History

456085e0dd131097fdf8c41862de0c934f914dc81631b017e1ce42c67f5a64d6 6648593 verified

0dd7112ff1723da48c310c7764dcf955eedf9246c3ec75932006e4584d35f8db ae03d0a verified

10635252fb85e1f5cc25b0281f0235b52ea6d0acecae3d258e9458f8beee7663 09c21bd verified

7f592f5e72da2956591c42252259999f70f6a8cd03ab47a7ebdb5908538ea2b3 b29eca9 verified

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Upload folder using huggingface_hub (#3) d0157ef

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initial commit 0499e0d

456085e0dd131097fdf8c41862de0c934f914dc81631b017e1ce42c67f5a64d6

6648593
verified

0dd7112ff1723da48c310c7764dcf955eedf9246c3ec75932006e4584d35f8db

ae03d0a
verified

10635252fb85e1f5cc25b0281f0235b52ea6d0acecae3d258e9458f8beee7663

09c21bd
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7f592f5e72da2956591c42252259999f70f6a8cd03ab47a7ebdb5908538ea2b3

b29eca9
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5b935628bc2d94ea952ace903929d1a9a3f92f7ee8790fc35af61f27d6fb77d9

24896d2
verified

Upload folder using huggingface_hub (#3)

d0157ef

Upload 4 files

0d3d57d

Upload folder using huggingface_hub (#1)

d5b985a

initial commit

0499e0d