Instructions to use manishw10/devgen-trocr-devanagari-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use manishw10/devgen-trocr-devanagari-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("paudelanil/trocr-devanagari-2") model = PeftModel.from_pretrained(base_model, "manishw10/devgen-trocr-devanagari-lora") - Transformers
How to use manishw10/devgen-trocr-devanagari-lora 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="manishw10/devgen-trocr-devanagari-lora")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("manishw10/devgen-trocr-devanagari-lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 325 Bytes
e74b0f8 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "ViTImageProcessor",
"image_std": [
0.5,
0.5,
0.5
],
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 224,
"width": 224
}
}
|