Instructions to use togethercomputer/Llama-2-7B-32K-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use togethercomputer/Llama-2-7B-32K-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="togethercomputer/Llama-2-7B-32K-Instruct")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("togethercomputer/Llama-2-7B-32K-Instruct")
model = AutoModelForCausalLM.from_pretrained("togethercomputer/Llama-2-7B-32K-Instruct")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use togethercomputer/Llama-2-7B-32K-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "togethercomputer/Llama-2-7B-32K-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "togethercomputer/Llama-2-7B-32K-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/togethercomputer/Llama-2-7B-32K-Instruct

SGLang

How to use togethercomputer/Llama-2-7B-32K-Instruct 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 "togethercomputer/Llama-2-7B-32K-Instruct" \
    --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": "togethercomputer/Llama-2-7B-32K-Instruct",
		"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 "togethercomputer/Llama-2-7B-32K-Instruct" \
        --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": "togethercomputer/Llama-2-7B-32K-Instruct",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use togethercomputer/Llama-2-7B-32K-Instruct with Docker Model Runner:
```
docker model run hf.co/togethercomputer/Llama-2-7B-32K-Instruct
```

Llama-2-7B-32K-Instruct

Commit History

Update config.json

d27380a
verified

arshzahed commited on Mar 28, 2024

Add _support_flash_attn_2 to Llama 2 32k Instruct (#19)

5a001e0
verified

arshzahed commited on Mar 27, 2024

Update added_tokens.json

a9fc7ba

juewang commited on Nov 17, 2023

Fast tokenizer

b050a6f

orangetin commited on Oct 3, 2023

Update README.md

35696b9

yuchenglu commited on Aug 18, 2023

Update README.md

4d80166

yuchenglu commited on Aug 18, 2023

Update README.md

e7f027c

yuchenglu commited on Aug 17, 2023

update model weights

e6bf8ab

Yucheng Lu commited on Aug 17, 2023

Update README.md

294d968

zhangce commited on Aug 17, 2023

Update README.md

6fd5a28

yuchenglu commited on Aug 17, 2023

update model weights to fp16; add bos token to config

a3e7bfc

Yucheng Lu commited on Aug 15, 2023

Update README.md

fd00afd

yuchenglu commited on Aug 14, 2023

Update README.md

c559461

yuchenglu commited on Aug 14, 2023