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

Libraries

How to use TheBloke/Falcon-7B-Instruct-GPTQ with Transformers:

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

pipe = pipeline("text-generation", model="TheBloke/Falcon-7B-Instruct-GPTQ", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("TheBloke/Falcon-7B-Instruct-GPTQ", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use TheBloke/Falcon-7B-Instruct-GPTQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TheBloke/Falcon-7B-Instruct-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/Falcon-7B-Instruct-GPTQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TheBloke/Falcon-7B-Instruct-GPTQ

SGLang

How to use TheBloke/Falcon-7B-Instruct-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/Falcon-7B-Instruct-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/Falcon-7B-Instruct-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/Falcon-7B-Instruct-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/Falcon-7B-Instruct-GPTQ",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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

Can't use with tgi. Getting `RuntimeError: weight transformer.h.0.self_attention.query_key_value.weight does not exist`

#12

by mpronesti - opened Jul 3, 2023

Discussion

mpronesti

Jul 3, 2023

•

edited Jul 3, 2023

Hi there!
I'm trying to use this model with text-generation-inference. Here's the script

volume=$PWD/data # share a volume with the Docker container to avoid downloading weights every run

docker run --gpus all --shm-size 2g -p 8080:80 -v $volume:/data \
ghcr.io/huggingface/text-generation-inference:latest \
--model-id TheBloke/falcon-7b-instruct-gptq \
--sharded false \
--quantize "gptq" \
--max-total-tokens 2048 \
--trust-remote-code

However, I get this error

RuntimeError: weight transformer.h.0.self_attention.query_key_value.weight does not exist

TheBloke

Owner Jul 8, 2023

Unfortunately Text Generation Inference have included a version of GPTQ that doesn't support most of the GPTQs currently on Hugging Face.

I hope to be able to release new GPTQs in future that will be compatible, but for now you'll need to see if there's another GPTQ that works with TGI, or make your own.

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