Instructions to use tanmayakaranth/matcha-chartqa-lora-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tanmayakaranth/matcha-chartqa-lora-adapter with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/matcha-base") model = PeftModel.from_pretrained(base_model, "tanmayakaranth/matcha-chartqa-lora-adapter") - Transformers
How to use tanmayakaranth/matcha-chartqa-lora-adapter with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tanmayakaranth/matcha-chartqa-lora-adapter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 335 Bytes
7888619 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"image_processor": {
"data_format": "channels_first",
"do_convert_rgb": true,
"do_normalize": true,
"image_processor_type": "Pix2StructImageProcessorFast",
"is_vqa": true,
"max_patches": 2048,
"patch_size": {
"height": 16,
"width": 16
}
},
"processor_class": "Pix2StructProcessor"
}
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