Instructions to use Firoj112/KVASIR_4bit_quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Firoj112/KVASIR_4bit_quantized with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/root/.cache/modelscope/hub/models/google/paligemma-3b-pt-224") model = PeftModel.from_pretrained(base_model, "Firoj112/KVASIR_4bit_quantized") - Notebooks
- Google Colab
- Kaggle
File size: 699 Bytes
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"_valid_processor_keys": [
"images",
"do_resize",
"size",
"resample",
"do_rescale",
"rescale_factor",
"do_normalize",
"image_mean",
"image_std",
"return_tensors",
"data_format",
"input_data_format",
"do_convert_rgb"
],
"do_convert_rgb": null,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "SiglipImageProcessor",
"image_seq_length": 256,
"image_std": [
0.5,
0.5,
0.5
],
"processor_class": "PaliGemmaProcessor",
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 224,
"width": 224
}
}
|