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 tokenizer.json from AhmadFareedKhan/model: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/AhmadFareedKhan/model/resolve/main/tokenizer.json
- Command line
-
hf download hf://AhmadFareedKhan/model/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/AhmadFareedKhan/model/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- c33e91d2995f3d41a38a0df45ea997681bd61b7594e7be5257aa431d1371f063
- Size of remote file:
- 17.1 MB
- SHA256:
- 4c08c80d1df11b82ada2fd707562f86a9ebd5b7de04f51ebd2b49f2cd5906d00
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