Instructions to use Mahmoud8/M-efficient_mlm_m0.40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud8/M-efficient_mlm_m0.40 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mahmoud8/M-efficient_mlm_m0.40")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mahmoud8/M-efficient_mlm_m0.40") model = AutoModelForSequenceClassification.from_pretrained("Mahmoud8/M-efficient_mlm_m0.40", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Mahmoud8/M-efficient_mlm_m0.40: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Mahmoud8/M-efficient_mlm_m0.40/resolve/main/training_args.bin
- Command line
-
hf download hf://Mahmoud8/M-efficient_mlm_m0.40/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mahmoud8/M-efficient_mlm_m0.40/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 0d9c8101a6aec01c6e3b6630f07c87695c9891ea9ef01d1b6eaa0f29e5467120
- Size of remote file:
- 3.96 kB
- SHA256:
- 0209b0002f1ae39d83fc3b9779e0e181c9ee561413970a8bbc4541e348a57a87
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