Instructions to use sachin/vit2distilgpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sachin/vit2distilgpt2 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="sachin/vit2distilgpt2")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("sachin/vit2distilgpt2") model = AutoModelForMultimodalLM.from_pretrained("sachin/vit2distilgpt2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c93880921b4452a8fa0b977e27992e9abb6a1b5f496047c06f5e17049c7bfe45
- Size of remote file:
- 743 MB
- SHA256:
- 797901e750d0f5d9f1b7731bade6012a52a819e37bc6b172156669790192b8f2
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