Instructions to use ChocoWu/nextgpt_7b_tiva_v0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ChocoWu/nextgpt_7b_tiva_v0 with Transformers:

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

pipe = pipeline("text-generation", model="ChocoWu/nextgpt_7b_tiva_v0")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ChocoWu/nextgpt_7b_tiva_v0")
model = AutoModelForCausalLM.from_pretrained("ChocoWu/nextgpt_7b_tiva_v0")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ChocoWu/nextgpt_7b_tiva_v0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ChocoWu/nextgpt_7b_tiva_v0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ChocoWu/nextgpt_7b_tiva_v0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ChocoWu/nextgpt_7b_tiva_v0

SGLang

How to use ChocoWu/nextgpt_7b_tiva_v0 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 "ChocoWu/nextgpt_7b_tiva_v0" \
    --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": "ChocoWu/nextgpt_7b_tiva_v0",
		"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 "ChocoWu/nextgpt_7b_tiva_v0" \
        --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": "ChocoWu/nextgpt_7b_tiva_v0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ChocoWu/nextgpt_7b_tiva_v0 with Docker Model Runner:
```
docker model run hf.co/ChocoWu/nextgpt_7b_tiva_v0
```

ChocoWu commited on Oct 4, 2023

Commit

9aa8ade

1 Parent(s): 742ef41

Update README.md

Browse files

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README.md +7 -1

README.md CHANGED Viewed

@@ -1,5 +1,11 @@
 ---
 license: cc-by-nc-sa-4.0
 ---
-  This model contains the weights of NExT-GPT covering text-image-video-audio (tiva), which is built upon 1) Vicuna-7B version-0, 2) ImageBind, 3) Stable Diffusion v1.5, 4) AudioLDM-l-full, and  5) ZeroScope v2_576w.
   For more details about the usage of the model, please refer to our [code repository](https://github.com/NExT-GPT/NExT-GPT).

 ---
 license: cc-by-nc-sa-4.0
 ---
+  This model contains the weights of NExT-GPT covering text-image-video-audio (tiva), which is built upon
+  - 1) [Vicuna-7B](https://huggingface.co/lmsys/vicuna-7b-delta-v0) with version 0
+  - 2) [ImageBind](https://dl.fbaipublicfiles.com/imagebind/imagebind_huge.pth)
+  - 3) [Stable Diffusion](https://huggingface.co/runwayml/stable-diffusion-v1-5) with version `v1-5`.
+  - 4) [AudioLDM](https://github.com/haoheliu/AudioLDM) with version `l-full`.
+  - 5) [ZeroScope](https://huggingface.co/cerspense/zeroscope_v2_576w) with version `v2_576w`.
   For more details about the usage of the model, please refer to our [code repository](https://github.com/NExT-GPT/NExT-GPT).