Instructions to use openbmb/MiniCPM-V with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use openbmb/MiniCPM-V with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("visual-question-answering", model="openbmb/MiniCPM-V", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("openbmb/MiniCPM-V", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Add requirements
Browse files
README.md
CHANGED
|
@@ -109,6 +109,15 @@ Click here to try out the Demo of [MiniCPM-V](http://120.92.209.146:80).
|
|
| 109 |
|
| 110 |
|
| 111 |
## Usage
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 112 |
|
| 113 |
```python
|
| 114 |
import torch
|
|
|
|
| 109 |
|
| 110 |
|
| 111 |
## Usage
|
| 112 |
+
Requirements: tested on python 3.10
|
| 113 |
+
```
|
| 114 |
+
Pillow==10.1.0
|
| 115 |
+
timm==0.9.10
|
| 116 |
+
torch==2.0.1
|
| 117 |
+
torchvision==0.15.2
|
| 118 |
+
transformers==4.36.0
|
| 119 |
+
sentencepiece==0.1.99
|
| 120 |
+
```
|
| 121 |
|
| 122 |
```python
|
| 123 |
import torch
|