Instructions to use kkatiz/THAI-BLIP-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kkatiz/THAI-BLIP-2 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="kkatiz/THAI-BLIP-2")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("kkatiz/THAI-BLIP-2") model = AutoModelForMultimodalLM.from_pretrained("kkatiz/THAI-BLIP-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bee0ac5285dcd478b40d0deec74901692099eb1982dd83f004d54f58f862cb09
- Size of remote file:
- 4.38 GB
- SHA256:
- 161c0b5a96d4711a7eb46ac14413bf6c76506a3d4bc6bca507114214be8f206c
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