metadata
license: mit
language:
- en
pipeline_tag: image-to-text
library_name: transformers
tags:
- medical record parsing
- lab report parsing
- prescription parsing
base_model:
- google/medgemma-4b-it
EkaCare Parrotlet-v-lite-4b
This is a purpose-built vision LLM specifically trained for the following downstream tasks on medical records in Indian healthcare context.
- Lab report parsing
- Digital prescription parsing
- Document classification
- PII extraction
A detailed description of this model can be obtained from this blog post.
Installation Requirements
To use this model, you need to install the following dependencies:
Python 3.10 and the following packages using pip:
pip install torch>=2.7.0 transformers>=4.52.0 pillow==11.3.0 huggingface_hub==0.36.0
Loading the model from Hugging Face Hub
from huggingface_hub import login
from transformers import AutoModel
login("hf_xxxxxxxxxxxxxxxxx")
repo_name = "ekacare/parrotlet-v-lite-4b"
model = AutoModel.from_pretrained(repo_name, trust_remote_code=True)
Parsing lab report
model.process("path/to/image", task="lab-report-parsing")
Task Types available
- lab-report-parsing
- prescription-parsing
- document-classification
- pii-parsing
License
This model is released under the MIT License, enabling broad use while maintaining attribution requirements.