Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use mahdishahsavari/Text-Classification-first-attempt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahdishahsavari/Text-Classification-first-attempt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mahdishahsavari/Text-Classification-first-attempt")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mahdishahsavari/Text-Classification-first-attempt") model = AutoModelForSequenceClassification.from_pretrained("mahdishahsavari/Text-Classification-first-attempt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 38b34cb50ba1deb1693caef05dfa2b574112d9f5d5d259fda182441512c9603a
- Size of remote file:
- 5.37 kB
- SHA256:
- aba368feb49216cfabbdaf3add65fcfc45628e009f27fef15ca1b78e05453a72
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