Instructions to use vamcrizer/model_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vamcrizer/model_classification with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("vamcrizer/model_classification") model = AutoModelForSeq2SeqLM.from_pretrained("vamcrizer/model_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2220344476a1ae3c3a12c89d2adf2782557fda96ce7cf69e5116a87a125e9fdb
- Size of remote file:
- 892 MB
- SHA256:
- 96d4345759f45ea5046ecb08f13514179e809ba53fa8a9bab1b8b00e14777338
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