Instructions to use lamm-mit/Cephalo-LaTeX-Phi-3-vision-128k-4b-beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lamm-mit/Cephalo-LaTeX-Phi-3-vision-128k-4b-beta 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="lamm-mit/Cephalo-LaTeX-Phi-3-vision-128k-4b-beta", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("lamm-mit/Cephalo-LaTeX-Phi-3-vision-128k-4b-beta", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
library_name: transformers
tags:
- latex
- image-to-text
datasets:
- lamm-mit/OleehyO-latex-formulas
- OleehyO/latex-formulas
license: apache-2.0
Model Summary
Cephalo is a series of multimodal materials science focused vision large language models (V-LLMs) designed to integrate visual and linguistic data for advanced understanding and interaction in human-AI or multi-agent AI frameworks.
Model Capabilities
This version of Cephalo, lamm-mit/Cephalo-LaTeX-Phi-3-vision-128k-4b-beta, is trained to convert images of equations to LaTeX code. This version is trained on a larger dataset and for more epochs than lamm-mit/Cephalo-LaTeX-Phi-3-vision-128k-4b-alpha.
