Instructions to use mllm-dev/t5_f_experiment_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mllm-dev/t5_f_experiment_4 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("mllm-dev/t5_f_experiment_4") model = AutoModelForSeq2SeqLM.from_pretrained("mllm-dev/t5_f_experiment_4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 034948d85e0a0f9e3f58038bb7170bf84814a98c91766bd5b0d8808283ff34bb
- Size of remote file:
- 484 MB
- SHA256:
- a6ade1571e03e1b5cc369c2ccc8ab6d24c04aa5d01676ebf1ce41d3936991685
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