Instructions to use braintacles/brainblip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use braintacles/brainblip 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="braintacles/brainblip")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("braintacles/brainblip") model = AutoModelForMultimodalLM.from_pretrained("braintacles/brainblip", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0c8e083440e9e5ccb8daec3526f003046a763c2cd14021366da28bd2134fad87
- Size of remote file:
- 1.88 GB
- SHA256:
- bed6c27f630b9bc35d5cf7ed0bd1aa92995524f27ba64f7fb21d2f94c0448650
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.