Instructions to use AhmadFareedKhan/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AhmadFareedKhan/model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="AhmadFareedKhan/model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("AhmadFareedKhan/model") model = AutoModelForMaskedLM.from_pretrained("AhmadFareedKhan/model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from AhmadFareedKhan/model: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/AhmadFareedKhan/model/resolve/main/training_args.bin
- Command line
-
hf download hf://AhmadFareedKhan/model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/AhmadFareedKhan/model/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 604049fd015a2eb2fcc369a86e763614b06f44c350435c87dc92f3ef42346958
- Size of remote file:
- 4.54 kB
- SHA256:
- 626bb82b3541904ea927690b03b3268e4d337ad2f70225bbda178a0e053c0e5a
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