Instructions to use mathigatti/vllm-instruct-amazon-description with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mathigatti/vllm-instruct-amazon-description with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mathigatti/vllm-instruct-amazon-description", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6523e61be123c09a7efeccf9bf91b5a28cf70c9afba2e76ea78cf3419a39b537
- Size of remote file:
- 5.69 kB
- SHA256:
- a6e99e882f2b3e7e13bfc63ff97b726f3b042267af654aee4b643bdcb374a12e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.