Instructions to use hf-internal-testing/tiny-random-OpenAIGPTForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-OpenAIGPTForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-OpenAIGPTForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-OpenAIGPTForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-OpenAIGPTForSequenceClassification") - Notebooks
- Google Colab
- Kaggle
File size: 186 Bytes
c513f7f | 1 2 3 4 5 6 7 8 | {
"model_max_length": 512,
"name_or_path": "temp/dummy/openai-gpt/processors",
"special_tokens_map_file": null,
"tokenizer_class": "OpenAIGPTTokenizer",
"unk_token": "<unk>"
}
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