Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use malcolm/TSC_SentimentA_IMDBAmznTSC_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use malcolm/TSC_SentimentA_IMDBAmznTSC_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="malcolm/TSC_SentimentA_IMDBAmznTSC_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("malcolm/TSC_SentimentA_IMDBAmznTSC_2") model = AutoModelForSequenceClassification.from_pretrained("malcolm/TSC_SentimentA_IMDBAmznTSC_2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 963d04b22fc30723a4f280ac995d6a608faa9851c1f92565dee28bf9b33befa0
- Size of remote file:
- 268 MB
- SHA256:
- e350a4975019b5264959ce3df174302e20a27472b8a6df4228d3eb9c21abddd0
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