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:
- 92a3c53bf4a05bcaebd598b971c8eeb2d484178b5f17caa08c616527f2cd856b
- Size of remote file:
- 4.73 GB
- SHA256:
- 45810c92e1fb7cd98d344010c5717a81d5fa0eb3590a34912bb70cc46fc7d2fa
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