Instructions to use shrg7/openvla-7b-string with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shrg7/openvla-7b-string with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="shrg7/openvla-7b-string", trust_remote_code=True)# Load model directly from transformers import AutoModelForVision2Seq model = AutoModelForVision2Seq.from_pretrained("shrg7/openvla-7b-string", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Upload processor
Browse files- preprocessor_config.json +1 -2
preprocessor_config.json
CHANGED
|
@@ -1,7 +1,6 @@
|
|
| 1 |
{
|
| 2 |
"auto_map": {
|
| 3 |
-
"AutoImageProcessor": "processing_prismatic.PrismaticImageProcessor"
|
| 4 |
-
"AutoProcessor": "processing_prismatic.PrismaticProcessor"
|
| 5 |
},
|
| 6 |
"image_processor_type": "PrismaticImageProcessor",
|
| 7 |
"image_resize_strategy": "resize-naive",
|
|
|
|
| 1 |
{
|
| 2 |
"auto_map": {
|
| 3 |
+
"AutoImageProcessor": "processing_prismatic.PrismaticImageProcessor"
|
|
|
|
| 4 |
},
|
| 5 |
"image_processor_type": "PrismaticImageProcessor",
|
| 6 |
"image_resize_strategy": "resize-naive",
|