Instructions to use jeff-RQ/new-test-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jeff-RQ/new-test-model with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="jeff-RQ/new-test-model")# Load model directly from transformers import AutoProcessor, AutoModelForVisualQuestionAnswering processor = AutoProcessor.from_pretrained("jeff-RQ/new-test-model") model = AutoModelForVisualQuestionAnswering.from_pretrained("jeff-RQ/new-test-model") - Notebooks
- Google Colab
- Kaggle
Update handler.py
Browse files- handler.py +1 -0
handler.py
CHANGED
|
@@ -2,6 +2,7 @@ from typing import Any, Dict
|
|
| 2 |
from transformers import Blip2Processor, Blip2ForConditionalGeneration
|
| 3 |
import io
|
| 4 |
from PIL import Image
|
|
|
|
| 5 |
|
| 6 |
class EndpointHandler:
|
| 7 |
def __init__(self, path=""):
|
|
|
|
| 2 |
from transformers import Blip2Processor, Blip2ForConditionalGeneration
|
| 3 |
import io
|
| 4 |
from PIL import Image
|
| 5 |
+
import base64
|
| 6 |
|
| 7 |
class EndpointHandler:
|
| 8 |
def __init__(self, path=""):
|