Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use aomar85/M3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aomar85/M3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aomar85/M3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aomar85/M3") model = AutoModelForSequenceClassification.from_pretrained("aomar85/M3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aomar85/M3: direct link, hf CLI and curl.
- Browser
- Download file 3.25 kB
-
https://huggingface.co/aomar85/M3/resolve/main/training_args.bin
- Command line
-
hf download hf://aomar85/M3/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aomar85/M3/resolve/main/training_args.bin
3.25 kB
- Xet hash:
- 56ebd608c3af305655a9de1ca372900165bcaae1642b31debfb3a4e6b2f88e44
- Size of remote file:
- 3.25 kB
- SHA256:
- 114f847e7e1a352debad80e97c5fdb2b39242cf04f21515eaec6da549399bbe6
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