Instructions to use EndLessTime/fine_tuned_per_domain_balanced_moe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EndLessTime/fine_tuned_per_domain_balanced_moe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="EndLessTime/fine_tuned_per_domain_balanced_moe")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("EndLessTime/fine_tuned_per_domain_balanced_moe") model = AutoModelForSequenceClassification.from_pretrained("EndLessTime/fine_tuned_per_domain_balanced_moe") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1c154fc9b6f6576101b176a4388c83baf0deaf56839c0ba2191b3e138a8df39a
- Size of remote file:
- 4.99 GB
- SHA256:
- 32aaaec990f4903d580f5a8bbbe8b324962b638f8f2b228f0686a882f0811833
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.