Instructions to use prodm93/T5Dynamic_title_model_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prodm93/T5Dynamic_title_model_v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("prodm93/T5Dynamic_title_model_v2") model = AutoModelForSeq2SeqLM.from_pretrained("prodm93/T5Dynamic_title_model_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from prodm93/T5Dynamic_title_model_v2: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/prodm93/T5Dynamic_title_model_v2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://prodm93/T5Dynamic_title_model_v2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/prodm93/T5Dynamic_title_model_v2/resolve/main/pytorch_model.bin
892 MB
- Xet hash:
- bd1d85d10240cf1b380c994d90eea79364cc8248f0f3375d742982e63a01dda2
- Size of remote file:
- 892 MB
- SHA256:
- 0d64b184f416ab91a77adcfb51b1587e4a5b1c30383bb533172a48bf70e51245
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