Instructions to use YanweiLi/MGM-13B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YanweiLi/MGM-13B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="YanweiLi/MGM-13B")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("YanweiLi/MGM-13B", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use YanweiLi/MGM-13B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "YanweiLi/MGM-13B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "YanweiLi/MGM-13B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/YanweiLi/MGM-13B
- SGLang
How to use YanweiLi/MGM-13B 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 "YanweiLi/MGM-13B" \ --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": "YanweiLi/MGM-13B", "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 "YanweiLi/MGM-13B" \ --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": "YanweiLi/MGM-13B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use YanweiLi/MGM-13B with Docker Model Runner:
docker model run hf.co/YanweiLi/MGM-13B
Update README.md
Browse files
README.md
CHANGED
|
@@ -8,7 +8,7 @@ datasets:
|
|
| 8 |
---
|
| 9 |
|
| 10 |
# MGM-13B Model Card
|
| 11 |
-
<a href='https://github.com/dvlab-research/
|
| 12 |
<a href='https://mini-gemini.github.io/'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
|
| 13 |
<a href='https://arxiv.org/pdf/2403.18814.pdf'><img src='https://img.shields.io/badge/Paper-Arxiv-red'></a>
|
| 14 |
|
|
@@ -36,7 +36,7 @@ Llama 2 is licensed under the LLAMA 2 Community License,
|
|
| 36 |
Copyright (c) Meta Platforms, Inc. All Rights Reserved.
|
| 37 |
|
| 38 |
**Where to send questions or comments about the model:**
|
| 39 |
-
https://github.com/dvlab-research/
|
| 40 |
|
| 41 |
## Intended use
|
| 42 |
**Primary intended uses:**
|
|
|
|
| 8 |
---
|
| 9 |
|
| 10 |
# MGM-13B Model Card
|
| 11 |
+
<a href='https://github.com/dvlab-research/MGM'><img src='https://img.shields.io/badge/Project-Code-violet'></a>
|
| 12 |
<a href='https://mini-gemini.github.io/'><img src='https://img.shields.io/badge/Project-Page-Green'></a>
|
| 13 |
<a href='https://arxiv.org/pdf/2403.18814.pdf'><img src='https://img.shields.io/badge/Paper-Arxiv-red'></a>
|
| 14 |
|
|
|
|
| 36 |
Copyright (c) Meta Platforms, Inc. All Rights Reserved.
|
| 37 |
|
| 38 |
**Where to send questions or comments about the model:**
|
| 39 |
+
https://github.com/dvlab-research/MGM/issues
|
| 40 |
|
| 41 |
## Intended use
|
| 42 |
**Primary intended uses:**
|