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
- Xet hash:
- 4ffb667fbd9b59156f2a5182c1748eaf8f5c48ef6224ad67e3c9a46e367bccfa
- Size of remote file:
- 2.72 MB
- SHA256:
- 9b78f582dabc34056303acf582b5b97a47ac32fa847bfeb33227c1a41681f760
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