Instructions to use andersonbcdefg/gte-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use andersonbcdefg/gte-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="andersonbcdefg/gte-tiny")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("andersonbcdefg/gte-tiny") model = AutoModel.from_pretrained("andersonbcdefg/gte-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from andersonbcdefg/gte-tiny: direct link, hf CLI and curl.
- Browser
- Download file 90.9 MB
-
https://huggingface.co/andersonbcdefg/gte-tiny/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://andersonbcdefg/gte-tiny/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/andersonbcdefg/gte-tiny/resolve/main/pytorch_model.bin
90.9 MB
- Xet hash:
- 68e46e8d928564f7bf4cef6d2f9bcd2cf8f54aa0663a679129cf64f3a4d74258
- Size of remote file:
- 90.9 MB
- SHA256:
- fb330a17e84f1bb20f861177f956b085e7d29b208921cb9b876a8b6f3dcbae3e
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