Instructions to use mllm-dev/gpt2_f_experiment_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mllm-dev/gpt2_f_experiment_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="mllm-dev/gpt2_f_experiment_4")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("mllm-dev/gpt2_f_experiment_4") model = AutoModelForSequenceClassification.from_pretrained("mllm-dev/gpt2_f_experiment_4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 68895bf2cd72da0dc9defb878474fb70b28bfbfa680366ead11da9b352835304
- Size of remote file:
- 996 MB
- SHA256:
- 371ebe61383bf96627d40fd145a8a58ff8cebd806764dfa3dd765e6e3f8cf8fc
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