Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use aomar85/M6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aomar85/M6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aomar85/M6")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aomar85/M6") model = AutoModelForSequenceClassification.from_pretrained("aomar85/M6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aomar85/M6: direct link, hf CLI and curl.
- Browser
- Download file 3.25 kB
-
https://huggingface.co/aomar85/M6/resolve/main/training_args.bin
- Command line
-
hf download hf://aomar85/M6/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aomar85/M6/resolve/main/training_args.bin
3.25 kB
- Xet hash:
- cc6c785ffa69d7ca9a6075da16587d60cb1885414d2777db2740ba6195542982
- Size of remote file:
- 3.25 kB
- SHA256:
- f79ecdac0d7f13cfc6eb9c2e710d0b95fe617fc404c83db7f4b35ba40dc99051
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