Instructions to use hf-tiny-model-private/tiny-random-DistilBertForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-DistilBertForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-tiny-model-private/tiny-random-DistilBertForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-tiny-model-private/tiny-random-DistilBertForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-tiny-model-private/tiny-random-DistilBertForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
Create README.md
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by tindeptrai - opened
README.md
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---
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license: mit
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datasets:
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- fka/awesome-chatgpt-prompts
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- allenai/dolma
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- nampdn-ai/tiny-strange-textbooks
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language:
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- vi
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metrics:
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- character
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pipeline_tag: table-question-answering
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tags:
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- climate
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---
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