Feature Extraction
Transformers
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use minsangK/m3-8192-5-epoch with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minsangK/m3-8192-5-epoch with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="minsangK/m3-8192-5-epoch")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("minsangK/m3-8192-5-epoch") model = AutoModel.from_pretrained("minsangK/m3-8192-5-epoch") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9b04270c7ee7fb5050fa5e66c55167731b22c5559a63083e303a456f565a4f57
- Size of remote file:
- 3.52 kB
- SHA256:
- 8da89fe01f996d18e7d511263212330f1256b4c938778ffaab4fe56f82b41dad
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.