ShareGPT4V: Improving Large Multi-Modal Models with Better Captions
Paper • 2311.12793 • Published • 18
How to use Lin-Chen/ShareGPT4V-13B_Pretrained_vit-large336-l12 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("feature-extraction", model="Lin-Chen/ShareGPT4V-13B_Pretrained_vit-large336-l12") # Load model directly
from transformers import AutoTokenizer, AutoModel
tokenizer = AutoTokenizer.from_pretrained("Lin-Chen/ShareGPT4V-13B_Pretrained_vit-large336-l12")
model = AutoModel.from_pretrained("Lin-Chen/ShareGPT4V-13B_Pretrained_vit-large336-l12")Model type: This is the vision tower of ShareGPT4V-13B fine-tuned with our ShareGPT4V dataset.
Model date: This vision tower was trained in Nov 2023.
Paper or resources for more information: [Project] [Paper] [Code]
Llama 2 is licensed under the LLAMA 2 Community License, Copyright (c) Meta Platforms, Inc. All Rights Reserved.
Primary intended uses: The primary use of this vision tower is research on large multimodal models and chatbots.
Primary intended users: The primary intended users of the model are researchers and hobbyists in computer vision, natural language processing, machine learning, and artificial intelligence.