Instructions to use wangjin2000/git-base-finetune-Aug142023_03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wangjin2000/git-base-finetune-Aug142023_03 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="wangjin2000/git-base-finetune-Aug142023_03")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("wangjin2000/git-base-finetune-Aug142023_03") model = AutoModelForMultimodalLM.from_pretrained("wangjin2000/git-base-finetune-Aug142023_03", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7cbb50cd8cedb8a08dca0630a8633d6d3227518beaca1045bfb5fe2b349fb3ee
- Size of remote file:
- 707 MB
- SHA256:
- 227ef026f99a45d5a554ba567c654288739b065c6265b79b75fe3e2399b353b2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.