Text Classification
Transformers
Safetensors
roberta
Generated from Trainer
multi-task-learning
Eval Results (legacy)
Instructions to use RonTon05/MTL_ATESG_Weighted with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RonTon05/MTL_ATESG_Weighted with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="RonTon05/MTL_ATESG_Weighted")# Load model directly from transformers import AutoTokenizer, PhoBERTMultiTask tokenizer = AutoTokenizer.from_pretrained("RonTon05/MTL_ATESG_Weighted") model = PhoBERTMultiTask.from_pretrained("RonTon05/MTL_ATESG_Weighted") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 926c7e505eb88a5c8a8e362176875c30dbf026f23bfdb2ec6b0c1fe5d85d72bd
- Size of remote file:
- 5.2 kB
- SHA256:
- fc97871f89f9f451fee108ae087fc5deccde276be99eaeb434e52b7ece983865
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.