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 pytorch_model.bin from Mahmoud8/M-efficient_mlm_m0.40: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/Mahmoud8/M-efficient_mlm_m0.40/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mahmoud8/M-efficient_mlm_m0.40/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mahmoud8/M-efficient_mlm_m0.40/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- dbe640f47ecf6d8affce18421accf0bdb20f09f687c047a4ad681492af1a86c4
- Size of remote file:
- 1.42 GB
- SHA256:
- 97ab40a5185563df849239ed0e7b13e68b24a286331ebe0d7d3bfdf5fd13d194
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