Instructions to use christopheparisse/complexity_92_reduced_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use christopheparisse/complexity_92_reduced_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="christopheparisse/complexity_92_reduced_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("christopheparisse/complexity_92_reduced_model") model = AutoModelForSequenceClassification.from_pretrained("christopheparisse/complexity_92_reduced_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): f6de2c4
Upload TFFlaubertForSequenceClassification
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README.md
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results: []
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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#
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This model is a fine-tuned version of [flaubert/flaubert_base_cased](https://huggingface.co/flaubert/flaubert_base_cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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tags:
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- generated_from_keras_callback
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- name: complexity_92_model
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results: []
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<!-- This model card has been generated automatically according to the information Keras had access to. You should
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# complexity_92_model
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This model is a fine-tuned version of [flaubert/flaubert_base_cased](https://huggingface.co/flaubert/flaubert_base_cased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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