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
```

AUTOGPTQ Error in Google Colab

#25

by echogit - opened Oct 13, 2023

Discussion

echogit

Oct 13, 2023

When trying to load the model in google colab, I get the error:

ImportError: Loading a GPTQ quantized model requires optimum (pip install optimum) and auto-gptq library (pip install auto-gptq)

My code has following:

!pip install -q -U transformers peft accelerate optimum
!pip install auto-gptq

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") #ERROR HAPPENS HERE

If I try a different 7b gptq model it does't give the error, for example:
model = AutoModelForCausalLM.from_pretrained("edumunozsala/llama-2-7b-int4-python-code-20k")

TheBloke

Owner Oct 14, 2023

Not sure why it's working with that other model and not this one. But please try installing AutoGPTQ as follows:

!pip install auto-gptq --extra-index-url https://huggingface.github.io/autogptq-index/whl/cu118/

GrigoryT22

Oct 15, 2023

as i understand error might be because transformers lib can not check existance of auto-gpt lib
_is_package_available function in transformers uses this code: "package_exists = importlib.util.find_spec(pkg_name) is not None"
the error might me in importlib lib, I cant find "util" module in it (Python 3.10.12, kaggle notebook)

Omkar008

Oct 25, 2023

yeah I am facing the same error ? But I got it working by using langchain Ctransformers .CTransformers(model="TheBloke/Llama-2-7b-Chat-GPTQ"). But still I want to download this model using pretrained and then use it like on a local hardware .

Omkar008

Oct 25, 2023

is there any solution ?

echogit

Oct 26, 2023

@TheBloke solution worked for me

aritrasen

Nov 3, 2023

Please help with this error.

from transformers import AutoTokenizer, pipeline, logging, AutoModelForCausalLM
#from auto_gptq import AutoGPTQForCausalLM, BaseQuantizeConfig

model_name_or_path = "TheBloke/Llama-2-7b-Chat-GPTQ"
model_basename = "model"

use_triton = False

tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, use_fast=True)

model = AutoModelForCausalLM.from_pretrained(model_name_or_path,
model_basename=model_basename,
use_safetensors=True,
trust_remote_code=True,
device="cuda:0",
use_triton=use_triton,
quantize_config=None)

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