EkaCare Public HealthCare LLMs
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How to use ekacare/parrotlet-v-lite-4b 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="ekacare/parrotlet-v-lite-4b", trust_remote_code=True) # Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ekacare/parrotlet-v-lite-4b", trust_remote_code=True, dtype="auto")This is a purpose-built vision LLM specifically trained for the following downstream tasks on medical records in Indian healthcare context.
A detailed description of this model can be obtained from this blog post.
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
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)
model.process("path/to/image", task="lab-report-parsing")
This model is released under the MIT License, enabling broad use while maintaining attribution requirements.