Image-Text-to-Text
Transformers
Safetensors
multilingual
internvl_chat
feature-extraction
internvl
vision
ocr
custom_code
Mixture of Experts
conversational
Instructions to use OpenGVLab/Mono-InternVL-2B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/Mono-InternVL-2B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="OpenGVLab/Mono-InternVL-2B", trust_remote_code=True) messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OpenGVLab/Mono-InternVL-2B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OpenGVLab/Mono-InternVL-2B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenGVLab/Mono-InternVL-2B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenGVLab/Mono-InternVL-2B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/OpenGVLab/Mono-InternVL-2B
- SGLang
How to use OpenGVLab/Mono-InternVL-2B 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 "OpenGVLab/Mono-InternVL-2B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenGVLab/Mono-InternVL-2B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "OpenGVLab/Mono-InternVL-2B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenGVLab/Mono-InternVL-2B", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use OpenGVLab/Mono-InternVL-2B with Docker Model Runner:
docker model run hf.co/OpenGVLab/Mono-InternVL-2B
Update README.md
Browse files
README.md
CHANGED
|
@@ -11,7 +11,6 @@ tags:
|
|
| 11 |
- internvl
|
| 12 |
- vision
|
| 13 |
- ocr
|
| 14 |
-
- video
|
| 15 |
- custom_code
|
| 16 |
---
|
| 17 |
|
|
@@ -84,7 +83,7 @@ Limitations: Although we have made efforts to ensure the safety of the model dur
|
|
| 84 |
|
| 85 |
## Quick Start
|
| 86 |
|
| 87 |
-
We provide an example code to run Mono-InternVL-2B using `transformers`.
|
| 88 |
|
| 89 |
> Please use transformers==4.37.2 to ensure the model works normally.
|
| 90 |
|
|
@@ -275,9 +274,9 @@ Mono-InternVL在性能上优于当前最先进的MLLM Mini-InternVL-2B-1.5,并
|
|
| 275 |
|
| 276 |
|
| 277 |
|
| 278 |
-
## 快速
|
| 279 |
|
| 280 |
-
我们提供了一个示例代码,用于使用 `transformers`
|
| 281 |
|
| 282 |
> 请使用 transformers==4.37.2 以确保模型正常运行。
|
| 283 |
|
|
|
|
| 11 |
- internvl
|
| 12 |
- vision
|
| 13 |
- ocr
|
|
|
|
| 14 |
- custom_code
|
| 15 |
---
|
| 16 |
|
|
|
|
| 83 |
|
| 84 |
## Quick Start
|
| 85 |
|
| 86 |
+
We provide an example code to run Mono-InternVL-2B inference using `transformers`.
|
| 87 |
|
| 88 |
> Please use transformers==4.37.2 to ensure the model works normally.
|
| 89 |
|
|
|
|
| 274 |
|
| 275 |
|
| 276 |
|
| 277 |
+
## 快速上手
|
| 278 |
|
| 279 |
+
我们提供了一个示例代码,用于使用 `transformers` 进行 Mono-InternVL-2B 推理。
|
| 280 |
|
| 281 |
> 请使用 transformers==4.37.2 以确保模型正常运行。
|
| 282 |
|