Instructions to use telsayed/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use telsayed/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="telsayed/test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("telsayed/test") model = AutoModelForMaskedLM.from_pretrained("telsayed/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from telsayed/test: direct link, hf CLI and curl.
- Browser
- Download file 440 MB
-
https://huggingface.co/telsayed/test/resolve/main/model.safetensors
- Command line
-
hf download hf://telsayed/test/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/telsayed/test/resolve/main/model.safetensors
440 MB
- Xet hash:
- 44172b48ce7a9d951000a9d76ae331b155df32c9fd4e93239a233d720f471725
- Size of remote file:
- 440 MB
- SHA256:
- 68d45e234eb4a928074dfd868cead0219ab85354cc53d20e772753c6bb9169d3
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