Instructions to use OpenGVLab/InternVL-14B-224px with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/InternVL-14B-224px with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="OpenGVLab/InternVL-14B-224px", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("OpenGVLab/InternVL-14B-224px", trust_remote_code=True) model = AutoModel.from_pretrained("OpenGVLab/InternVL-14B-224px", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -25,6 +25,7 @@ It is _**the largest open-source vision/vision-language foundation model (14B)**
|
|
| 25 |
|
| 26 |
## Model Details
|
| 27 |
- **Model Type:** vision-language foundation model
|
|
|
|
| 28 |
- **Model Stats:**
|
| 29 |
- Params: 14B
|
| 30 |
- Image size: 224 x 224
|
|
|
|
| 25 |
|
| 26 |
## Model Details
|
| 27 |
- **Model Type:** vision-language foundation model
|
| 28 |
+
- **Support Tasks:** zero-shot image/video classification, image-text/video retrieval, image captioning
|
| 29 |
- **Model Stats:**
|
| 30 |
- Params: 14B
|
| 31 |
- Image size: 224 x 224
|