Visual Question Answering
Transformers
Safetensors
English
Chinese
minicpmv
feature-extraction
custom_code
Eval Results
Instructions to use openbmb/MiniCPM-V-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-V-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="openbmb/MiniCPM-V-2", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-V-2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update readme
Browse files- README.md +2 -2
- assets/london_car.gif +3 -0
README.md
CHANGED
|
@@ -51,8 +51,8 @@ We deploy MiniCPM-V 2.0 on end devices. The demo video is the raw screen recordi
|
|
| 51 |
<table align="center">
|
| 52 |
<p align="center">
|
| 53 |
<img src="assets/station.gif" width=40% style="display:inline-block;"/>
|
| 54 |
-
<img src="assets/
|
| 55 |
-
|
| 56 |
</table>
|
| 57 |
|
| 58 |
|
|
|
|
| 51 |
<table align="center">
|
| 52 |
<p align="center">
|
| 53 |
<img src="assets/station.gif" width=40% style="display:inline-block;"/>
|
| 54 |
+
<img src="assets/london_car.gif" width=40% style="display:inline-block;"/>
|
| 55 |
+
</p>
|
| 56 |
</table>
|
| 57 |
|
| 58 |
|
assets/london_car.gif
ADDED
|
Git LFS Details
|