Instructions to use OneFly7/bge_m3_pointwise_bs16_lr1e5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OneFly7/bge_m3_pointwise_bs16_lr1e5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="OneFly7/bge_m3_pointwise_bs16_lr1e5")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("OneFly7/bge_m3_pointwise_bs16_lr1e5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from OneFly7/bge_m3_pointwise_bs16_lr1e5: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/OneFly7/bge_m3_pointwise_bs16_lr1e5/resolve/main/tokenizer.json
- Command line
-
hf download hf://OneFly7/bge_m3_pointwise_bs16_lr1e5/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/OneFly7/bge_m3_pointwise_bs16_lr1e5/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 4786592ea7559ad79ac9adb5350927747fb7d0e28b608784f8cf9cd36906c228
- Size of remote file:
- 17.1 MB
- SHA256:
- 5df1f55d60c9705a501ab9a75550728625740741fe4be308dac4806c16b7d51d
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