Model Details

• Model Name: Git-base-One-Piece
• Base Model: Microsoft's "git-base" model
• Model Type: Generative Image-to-Text (GIT)
• Fine-Tuned On: 'One-Piece-anime-captions' dataset
• Fine-Tuning Purpose: To generate text captions for images related to the anime series "One Piece."

Model Description

Git-base-One-Piece is a fine-tuned variant of Microsoft's git-base model, specifically trained for the task of generating descriptive text captions for images from the One-Piece-anime-captions dataset.

The dataset consists of 856 {image: caption} pairs, providing a substantial and diverse training corpus for the model.

The model is conditioned on both CLIP image tokens and text tokens and employs a teacher forcing training approach. It predicts the next text token while considering the context provided by the image and previous text tokens.

Limitations

• The quality of generated captions may vary depending on the complexity and diversity of images from the One-Piece-anime-captions dataset.
• The model's output is based on the data it was fine-tuned on, so it may not generalize well to images outside the dataset's domain. Generating highly detailed or contextually accurate captions may still be a challenge.

Usage

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-to-text", model="ayoubkirouane/git-base-One-Piece")

or

# Load model directly
from transformers import AutoProcessor, AutoModelForCausalLM

processor = AutoProcessor.from_pretrained("ayoubkirouane/git-base-One-Piece")
model = AutoModelForCausalLM.from_pretrained("ayoubkirouane/git-base-One-Piece")