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, device_map="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
```

TheBloke commited on May 27, 2023

Commit

7c6a3ac

1 Parent(s): 60a0b33

Initial AutoGPTQ model commit.

Browse files

Files changed (1) hide show

README.md +4 -0

README.md CHANGED Viewed

@@ -34,15 +34,19 @@ I have [opened a PR here](https://github.com/oobabooga/text-generation-webui/pul
 To get it working before the PR is merged, you will need to:
 1. Edit `text-generation-webui/modules/AutoGPTQ_loader.py`
 2. Make the following change:
 Find the line that says:
 ```
 'use_safetensors': use_safetensors,
 ```
 And after it, add:
 ```
 'trust_remote_code': shared.args.trust_remote_code,
 ```
 [Once you are done the file should look like this](https://github.com/oobabooga/text-generation-webui/blob/473a57e35219c063d2fc230cfc7b5a118b448b38/modules/AutoGPTQ_loader.py#L33-L39)
 3. Then save and close the file, and launch text-generation-webui as described below
 ## How to download and use this model in text-generation-webui

 To get it working before the PR is merged, you will need to:
 1. Edit `text-generation-webui/modules/AutoGPTQ_loader.py`
 2. Make the following change:
 Find the line that says:
 ```
 'use_safetensors': use_safetensors,
 ```
 And after it, add:
 ```
 'trust_remote_code': shared.args.trust_remote_code,
 ```
 [Once you are done the file should look like this](https://github.com/oobabooga/text-generation-webui/blob/473a57e35219c063d2fc230cfc7b5a118b448b38/modules/AutoGPTQ_loader.py#L33-L39)
 3. Then save and close the file, and launch text-generation-webui as described below
 ## How to download and use this model in text-generation-webui