Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
text-embeddings-inference
Instructions to use afiqlol/Malay-Sentiment3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use afiqlol/Malay-Sentiment3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="afiqlol/Malay-Sentiment3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("afiqlol/Malay-Sentiment3") model = AutoModelForSequenceClassification.from_pretrained("afiqlol/Malay-Sentiment3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f321d8c5ac128587667f5a7573659ddb9b400ac1a5e64899c0ca18f54aca8364
- Size of remote file:
- 17.1 MB
- SHA256:
- dd3dab32821a0cde2f7059b9704a9b9a269840c0b485fe1aeb86730ea0edcd77
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.