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

Libraries

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

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

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

Install from pip and serve model

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

Use Docker

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

SGLang

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

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

Can't determine model type from model name. Please specify it manually using --model_type argument

#12

by chouaibmeramria - opened Apr 30, 2023

Discussion

chouaibmeramria

Apr 30, 2023

after model download i get this message

Can't determine model type from model name. Please specify it manually using --model_type argument

TheBloke

Owner Apr 30, 2023

So did you specify the model type in the GPTQ settings?

Try following my easy install instructions. I think it's step 8 you're not doing fully.

How to easily download and use this model in text-generation-webui

Open the text-generation-webui UI as normal.

Click the Model tab.
Under Download custom model or LoRA, enter TheBloke/wizardLM-7B-GPTQ.
Click Download.
Wait until it says it's finished downloading.
Click the Refresh icon next to Model in the top left.
In the Model drop-down: choose the model you just downloaded,wizardLM-7B-GPTQg.
If you see an error in the bottom right, ignore it - it's temporary.
Fill out the GPTQ parameters on the right: Bits = 4, Groupsize = 128, model_type = Llama
Click Save settings for this model in the top right.
Click Reload the Model in the top right.
Once it says it's loaded, click the Text Generation tab and enter a prompt!

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

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