Instructions to use hf-internal-testing/tiny-random-XLMRobertaXLForSequenceClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-XLMRobertaXLForSequenceClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="hf-internal-testing/tiny-random-XLMRobertaXLForSequenceClassification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-XLMRobertaXLForSequenceClassification") model = AutoModelForSequenceClassification.from_pretrained("hf-internal-testing/tiny-random-XLMRobertaXLForSequenceClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- be01d38cebd17b982cac9f89c22ed936ca23a490b2718b7aeebfe27c0827b0fe
- Size of remote file:
- 32.2 MB
- SHA256:
- 987abc2a0db1fd8e261db58e7d02bde73dfb118ebe2264c038b5aec39fcde41b
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