Update README.md

README.md

@@ -9,3 +9,46 @@ model_name: microsoft/git-base
 pipeline_tag: image-to-text
 library_name: transformers
 ---
+
+
+# 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 
+
+```python
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+
+pipe = pipeline("image-to-text", model="ayoubkirouane/git-base-One-Piece")
+```
+
+**or**
+
+```python
+# 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")
+```