Instructions to use leffff/ruBert-base-response-quality with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leffff/ruBert-base-response-quality with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="leffff/ruBert-base-response-quality")# Load model directly from transformers import AutoTokenizer, AutoModelForNextSentencePrediction tokenizer = AutoTokenizer.from_pretrained("leffff/ruBert-base-response-quality") model = AutoModelForNextSentencePrediction.from_pretrained("leffff/ruBert-base-response-quality") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:4be2ec4a5acd7dc319069f2deec54887048d7e11bc9d221af46b4dec4992d0c5
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size 713259032
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