Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use nonsodev/datrix-text-classification-job_81d898e0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nonsodev/datrix-text-classification-job_81d898e0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nonsodev/datrix-text-classification-job_81d898e0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nonsodev/datrix-text-classification-job_81d898e0") model = AutoModelForSequenceClassification.from_pretrained("nonsodev/datrix-text-classification-job_81d898e0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Fix: exclude token_type_ids from model_input_names
Browse files- tokenizer_config.json +6 -2
tokenizer_config.json
CHANGED
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@@ -11,5 +11,9 @@
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]"
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"strip_accents": null,
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"tokenize_chinese_chars": true,
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"tokenizer_class": "BertTokenizer",
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"unk_token": "[UNK]",
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"model_input_names": [
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"input_ids",
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"attention_mask"
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]
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}
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