Instructions to use pedropei/question-intimacy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pedropei/question-intimacy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pedropei/question-intimacy")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pedropei/question-intimacy") model = AutoModelForSequenceClassification.from_pretrained("pedropei/question-intimacy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from pedropei/question-intimacy: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/pedropei/question-intimacy/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://pedropei/question-intimacy/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/pedropei/question-intimacy/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- 76a22da44b375d03794ff5e2567088fd27f187edf637c77b4f66aa49ca506f74
- Size of remote file:
- 499 MB
- SHA256:
- d70c3d98241e00c7e8b3b2af7329a708260d564a20f91e7bdd037ff83f36f2f4
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