Instructions to use agiagoulas/bert-pss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use agiagoulas/bert-pss with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="agiagoulas/bert-pss")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("agiagoulas/bert-pss") model = AutoModelForSequenceClassification.from_pretrained("agiagoulas/bert-pss", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from agiagoulas/bert-pss: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/agiagoulas/bert-pss/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://agiagoulas/bert-pss/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/agiagoulas/bert-pss/resolve/main/flax_model.msgpack
438 MB
- Xet hash:
- e50e990507d9123fb774019ab51fd377d72f93bf87b2894fcf7daf0d909d85e7
- Size of remote file:
- 438 MB
- SHA256:
- e4f563ca565f57852708fbcec89b3161e06007374ba3058deb938f709169806e
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