Text Classification
Transformers
PyTorch
TensorBoard
Thai
camembert
sentiment-analysis
text-embeddings-inference
Instructions to use poom-sci/WangchanBERTa-finetuned-sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use poom-sci/WangchanBERTa-finetuned-sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="poom-sci/WangchanBERTa-finetuned-sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("poom-sci/WangchanBERTa-finetuned-sentiment") model = AutoModelForSequenceClassification.from_pretrained("poom-sci/WangchanBERTa-finetuned-sentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dc897d92efb650947183605d6bf8852778470ad1ff95b2bfc722325d26aadcf2
- Size of remote file:
- 421 MB
- SHA256:
- b941596317023db9eba4608ad3d0d019574320181b25c4aec75410c1ae4dbf4d
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