Image-to-Text
Transformers
PyTorch
TensorBoard
vision-encoder-decoder
image-text-to-text
Generated from Trainer
Instructions to use larabe/news with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use larabe/news 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="larabe/news")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("larabe/news") model = AutoModelForMultimodalLM.from_pretrained("larabe/news", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from larabe/news: direct link, hf CLI and curl.
- Browser
- Download file 4.02 MB
-
https://huggingface.co/larabe/news/resolve/refs%2Fpr%2F1/tokenizer.json
- Command line
-
hf download hf://larabe/news@refs/pr/1/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/larabe/news/resolve/refs%2Fpr%2F1/tokenizer.json
4.02 MB
File too large to display, you can check the raw version instead.