Sentence Similarity
Transformers
Safetensors
English
distilbert
text-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use kweinmeister/distilbert-snli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kweinmeister/distilbert-snli with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kweinmeister/distilbert-snli") model = AutoModelForSequenceClassification.from_pretrained("kweinmeister/distilbert-snli") - Notebooks
- Google Colab
- Kaggle
Model Card for distilbert-snli
Model Details
Model Description
A fine-tuned version of distilbert/distilbert-base-uncased using the stanford-nlp/snli dataset.
- Developed by: Karl Weinmeister
- Language(s) (NLP): en
- License: apache-2.0
- Finetuned from model [optional]: distilbert/distilbert-base-uncased
Training Hyperparameters
- Training regime: The model was trained for 5 epochs with batch size 128.
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Model tree for kweinmeister/distilbert-snli
Base model
distilbert/distilbert-base-uncasedEvaluation results
- accuracy on stanford-nlp/snliself-reported0.898