Instructions to use Mahmoud8/efficient_mlm_m0.40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mahmoud8/efficient_mlm_m0.40 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Mahmoud8/efficient_mlm_m0.40")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Mahmoud8/efficient_mlm_m0.40") model = AutoModelForSequenceClassification.from_pretrained("Mahmoud8/efficient_mlm_m0.40", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Mahmoud8/efficient_mlm_m0.40: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/Mahmoud8/efficient_mlm_m0.40/resolve/main/training_args.bin
- Command line
-
hf download hf://Mahmoud8/efficient_mlm_m0.40/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Mahmoud8/efficient_mlm_m0.40/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 37374bfdf47ede88926a10d7e226a6080d85b171e125765f873223a896fbf13f
- Size of remote file:
- 3.96 kB
- SHA256:
- 7e6c76e37b193be723724ec2b9b45ea524ef75a3ee909aa4b37ca60c948c90d2
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