Instructions to use adriansanz/rerank_v7_5_ep with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adriansanz/rerank_v7_5_ep with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="adriansanz/rerank_v7_5_ep")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("adriansanz/rerank_v7_5_ep") model = AutoModelForSequenceClassification.from_pretrained("adriansanz/rerank_v7_5_ep", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from adriansanz/rerank_v7_5_ep: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/adriansanz/rerank_v7_5_ep/resolve/main/tokenizer.json
- Command line
-
hf download hf://adriansanz/rerank_v7_5_ep/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/adriansanz/rerank_v7_5_ep/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- e6741ee3511f179030bd5bd94047af41a0557149618a695de8175e2230adf84b
- Size of remote file:
- 17.1 MB
- SHA256:
- 222975faa02f5257c6e8c734e85973e48c8d42d7d37d90b894c73efa1841d76a
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