Instructions to use AlexKoff88/bert_nm_mnli_sparse_quantized_90 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AlexKoff88/bert_nm_mnli_sparse_quantized_90 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="AlexKoff88/bert_nm_mnli_sparse_quantized_90")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AlexKoff88/bert_nm_mnli_sparse_quantized_90") model = AutoModelForSequenceClassification.from_pretrained("AlexKoff88/bert_nm_mnli_sparse_quantized_90") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f9b8158ea013121afa9da106305e9829f9f4fc1f601a6ef15237e7985f25ac2
- Size of remote file:
- 182 MB
- SHA256:
- b269a13702b9bdc2c2fbe74290946da7a547b4105bc695a0d47ec9e1c75f60fa
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