Instructions to use fgaim/tielectra-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fgaim/tielectra-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="fgaim/tielectra-small")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("fgaim/tielectra-small") model = AutoModelForMaskedLM.from_pretrained("fgaim/tielectra-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fgaim/tielectra-small: direct link, hf CLI and curl.
- Browser
- Download file 54.3 MB
-
https://huggingface.co/fgaim/tielectra-small/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fgaim/tielectra-small/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fgaim/tielectra-small/resolve/main/pytorch_model.bin
54.3 MB
- Xet hash:
- ca781fd798c1fb53e43ee278e6dc28402773f15854ecbda06803273e74d542c3
- Size of remote file:
- 54.3 MB
- SHA256:
- d83431429428ed1e5e372aa50b6590d6077e220c73a0ea4de9590cc60f7b37bb
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