Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use muhammadravi251001/checkpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use muhammadravi251001/checkpoint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="muhammadravi251001/checkpoint")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("muhammadravi251001/checkpoint") model = AutoModelForSequenceClassification.from_pretrained("muhammadravi251001/checkpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 79f0144c6ab8313e8f6379e5f0285225862e01ff88be4e29a998998bf6758cb7
- Size of remote file:
- 3.64 kB
- SHA256:
- 5e673f2e133da4137d2c4f2b89e0b34a4f4b7e113490881c214c8a0c205c6cdd
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