Text Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Trained with AutoTrain
text-embeddings-inference
Instructions to use guess-winnow/bhasa-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use guess-winnow/bhasa-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="guess-winnow/bhasa-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("guess-winnow/bhasa-sentiment") model = AutoModelForSequenceClassification.from_pretrained("guess-winnow/bhasa-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e1253493d15a639ba9752d32bf296dd6f3be1f27afdea2df6ac3e1c9e884224a
- Size of remote file:
- 5.37 kB
- SHA256:
- 56b0a3f05c9f7962009ba0aa65901b7c0d94d867a284cef80d1cd2f464af8e58
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.