This is a 4-bit AWQ quantized version of rednote-hilab/dots.ocr.
Modellquelle
Quellenbeschreibung
This is a 4-bit AWQ quantized version of rednote-hilab/dots.ocr.
Quellen
1 QuelleVerifiziert 11. Sept.
Modellartefakte
1 ArtefaktQuellenauszüge
2 Auszüge--- license: apache-2.0 base_model: rednote-hilab/dots.ocr tags: - ocr - vision - quantized - awq - 4bit library_name: transformers pipeline_tag: image-to-text --- # dots.ocr AWQ 4-bit Quantized This is a 4-bit AWQ quantized version of [rednote-hilab/dots.ocr](https://huggingface.co/rednote-hilab/dots.ocr). ## Model Details - **Base Model**: rednote-hilab/dots.ocr - **Quantization**: W4A16 (4-bit weights, 16-bit activations) - **Method**: llm-compressor - **Size**: ~1.5GB (reduced from ~6GB) ## Usage ```python from transformers import AutoModelForCausalLM, AutoTokenizer, AutoProcessor model = AutoModelForCausalLM.from_pretrained( "sugam24/dots-ocr-awq-4bit", trust_remote_code=True, device_map="cuda" ) tokenizer = AutoTokenizer.from_pretrained("sugam24/dots-ocr-awq-4bit", trust_remote_code=True) processor = AutoProcessor.from_pretrained("sugam24/dots-ocr-awq-4bit", trust_remote_code=True) ``` ## License Same as the base model (Apache 2.0).
from transformers import AutoModelForCausalLM, AutoTokenizer, AutoProcessor
model = AutoModelForCausalLM.from_pretrained(
"sugam24/dots-ocr-awq-4bit",
trust_remote_code=True,
device_map="cuda"
)
tokenizer = AutoTokenizer.from_pretrained("sugam24/dots-ocr-awq-4bit", trust_remote_code=True)
processor = AutoProcessor.from_pretrained("sugam24/dots-ocr-awq-4bit", trust_remote_code=True)
Same as the base model (Apache 2.0).
Source context: 57 downloads · 1 likes · Pipeline image-to-text · Library transformers · Repo sugam24/dots-ocr-awq-4bit