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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("runaksh/ResumeClassification_distilBERT") model = AutoModelForSequenceClassification.from_pretrained("runaksh/ResumeClassification_distilBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.68ab03e
-
Upload tokenizer
029e8bc -
Upload DistilBertForSequenceClassification
20ba403
-
Upload tokenizer
75f47d8 -
Upload DistilBertForSequenceClassification
713ac00 -
Upload tokenizer
9b562e2 -
Upload DistilBertForSequenceClassification
dafdad5 -
Upload tokenizer
25c0141 -
Upload DistilBertForSequenceClassification
fcf1476 -
initial commit
1f6422f