Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use aomar85/M2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aomar85/M2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="aomar85/M2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("aomar85/M2") model = AutoModelForSequenceClassification.from_pretrained("aomar85/M2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from aomar85/M2: direct link, hf CLI and curl.
- Browser
- Download file 3.31 kB
-
https://huggingface.co/aomar85/M2/resolve/main/training_args.bin
- Command line
-
hf download hf://aomar85/M2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/aomar85/M2/resolve/main/training_args.bin
3.31 kB
- Xet hash:
- 247e113b756476800bfd40b0ec7889627cd016d42ad7d0a2cabbf9f9e8cf1978
- Size of remote file:
- 3.31 kB
- SHA256:
- f3b86c45ea30036826eb8d97462664402eb4ee9fdebec66afbedee982a926514
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