Instructions to use kusumakar/hashtagGenerater with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kusumakar/hashtagGenerater 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="kusumakar/hashtagGenerater")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("kusumakar/hashtagGenerater") model = AutoModelForMultimodalLM.from_pretrained("kusumakar/hashtagGenerater", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68212b447fcfed78bca6cdd560e7c7f063ee9455914ce016a8dad90082d748c0
- Size of remote file:
- 982 MB
- SHA256:
- 75629ca0822bf3363c7bc48aaea869e21903fe0e971e6da3dd8241eb988548cb
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