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 pytorch_model.bin from Mahmoud8/efficient_mlm_m0.40: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/Mahmoud8/efficient_mlm_m0.40/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Mahmoud8/efficient_mlm_m0.40/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Mahmoud8/efficient_mlm_m0.40/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- bb7067ab53952654a2dc9b36234ba4aef8a20be6432f7c836f567c86c2ac92d2
- Size of remote file:
- 1.42 GB
- SHA256:
- 9669267c765d46d29dcdc8d2c3855c7ab0645bd6adbd55347245ee021882d1af
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