Instructions to use tnkchaseme/DeepSeek-OCR-2-CROHME-LORA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use tnkchaseme/DeepSeek-OCR-2-CROHME-LORA with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("deepseek-ai/DeepSeek-OCR-2") model = PeftModel.from_pretrained(base_model, "tnkchaseme/DeepSeek-OCR-2-CROHME-LORA") - Transformers
How to use tnkchaseme/DeepSeek-OCR-2-CROHME-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="tnkchaseme/DeepSeek-OCR-2-CROHME-LORA")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tnkchaseme/DeepSeek-OCR-2-CROHME-LORA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Upload folder using huggingface_hub
Browse files
README.md
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---
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base_model: deepseek-ai/DeepSeek-OCR-2
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library_name: peft
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pipeline_tag: image-
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tags:
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- base_model:adapter:deepseek-ai/DeepSeek-OCR-2
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- lora
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---
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base_model: deepseek-ai/DeepSeek-OCR-2
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library_name: peft
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pipeline_tag: image-to-text
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tags:
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- base_model:adapter:deepseek-ai/DeepSeek-OCR-2
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- lora
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