Instructions to use TheBloke/Llama-2-7B-Chat-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheBloke/Llama-2-7B-Chat-GPTQ with Transformers:

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

pipe = pipeline("text-generation", model="TheBloke/Llama-2-7B-Chat-GPTQ")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TheBloke/Llama-2-7B-Chat-GPTQ")
model = AutoModelForCausalLM.from_pretrained("TheBloke/Llama-2-7B-Chat-GPTQ", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TheBloke/Llama-2-7B-Chat-GPTQ with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/TheBloke/Llama-2-7B-Chat-GPTQ

SGLang

How to use TheBloke/Llama-2-7B-Chat-GPTQ 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 "TheBloke/Llama-2-7B-Chat-GPTQ" \
    --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": "TheBloke/Llama-2-7B-Chat-GPTQ",
		"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 "TheBloke/Llama-2-7B-Chat-GPTQ" \
        --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": "TheBloke/Llama-2-7B-Chat-GPTQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TheBloke/Llama-2-7B-Chat-GPTQ with Docker Model Runner:
```
docker model run hf.co/TheBloke/Llama-2-7B-Chat-GPTQ
```

TheBloke/Llama-2-7b-(Chat-)GPTQ repeats request

#22

by hyzhak - opened Sep 30, 2023

Discussion

hyzhak

Sep 30, 2023

•

edited Sep 30, 2023

Hi team,

I'm passing request to the LLM model and it repeats my request (with slight variation) and add response to it. Is it expected?

revision: gptq-4bit-32g-actorder_True
do_sample: True
temperature: 0.25
repetition_penalty: 1.2
max_new_tokens: 512

Example (I tried use instruction like [INST] but it didn't help).

Input:

Please write a haiku about llama

output from TheBloke/Llama-2-7b-Chat-GPTQ:

Please write a haiku about llama-ing.

Here is my attempt:
Llama's gentle glow,
Softly grazes the landscape,
Serenity found.

output from TheBloke/Llama-2-7b-GPTQ:

Please write a haiku about llama.
I'll start:
Llama is my friend,
He lives in the zoo.
His name is Llamalot!
Reactions: Squirrel_and_Bird and TigerTankFan

Is there any way to prevent Llama2 to repeat request, since like in a case with "llama-ing" it isn't no only removing few similar characters at the beginning, sometimes it could be more.

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