Instructions to use SRDdev/Nebula with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SRDdev/Nebula 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="SRDdev/Nebula")# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("SRDdev/Nebula") model = AutoModelForImageTextToText.from_pretrained("SRDdev/Nebula") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 37f8720ea74d264c7684784853283d17905060b895682779f505ac414463a258
- Size of remote file:
- 896 MB
- SHA256:
- f76f83fe6e67313f85b90fab7504558eba18f8c695412085e7fa30454c971ba1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.