Image-to-Text
Transformers
Safetensors
English
vision-encoder-decoder
image-text-to-text
vision
text-generation
medical
chest-xray
healthcare
multimodal
Instructions to use Molkaatb/ChestX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Molkaatb/ChestX 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="Molkaatb/ChestX")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Molkaatb/ChestX") model = AutoModelForMultimodalLM.from_pretrained("Molkaatb/ChestX", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Molkaatb/ChestX: direct link, hf CLI and curl.
- Browser
- Download file 2.11 MB
-
https://huggingface.co/Molkaatb/ChestX/resolve/main/tokenizer.json
- Command line
-
hf download hf://Molkaatb/ChestX/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Molkaatb/ChestX/resolve/main/tokenizer.json
2.11 MB
File too large to display, you can check the raw version instead.