Instructions to use helizac/dots.ocr-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use helizac/dots.ocr-4bit 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="helizac/dots.ocr-4bit", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("helizac/dots.ocr-4bit", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
How is the model supposed to be deployed with vLLM?
When I tried to deploy the model with VLLM, there is error AttributeError: Model DotsOCRForCausalLM does not support BitsAndBytes quantization yet. No 'packed_modules_mapping' found
Was faced with the same issue
Hello, sorry for late response.
Currently, vllm is not supporting dots.ocr ( DotsOCRForCausalLM ). If there is any update, I can update this model or release a similar model that supports vllm as well.
You might follow as:
https://huggingface.co/rednote-hilab/dots.ocr/discussions/20
Same issue. It seems the PR has been merged into vLLM 4 days ago.
The latest vllm nightly build wheel has support dots_ocr and can use bitsandbytes inflight.
using vllm 0.13.0 load this model, but have error like: self.data.shape == loaded_weight.shape
any idea how i implement via llama_cpp ?
seem there is no compatible chathandler...