Instructions to use runaksh/ResumeClassification_distilBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use runaksh/ResumeClassification_distilBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="runaksh/ResumeClassification_distilBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("runaksh/ResumeClassification_distilBERT") model = AutoModelForSequenceClassification.from_pretrained("runaksh/ResumeClassification_distilBERT") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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 sha256:35f9f4ea9a52a42d0714e52717687664423a936328d2393289c1708cdd933219
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size 267903316
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