Instructions to use kmok1/cs_m2m_2e-5_500_v0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kmok1/cs_m2m_2e-5_500_v0.2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("kmok1/cs_m2m_2e-5_500_v0.2") model = AutoModelForSeq2SeqLM.from_pretrained("kmok1/cs_m2m_2e-5_500_v0.2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3e4ebff17bf214f3258b544b6ecb5a40a9f9b445d94f5aa17b2143e5915ac96b
- Size of remote file:
- 5.05 kB
- SHA256:
- fe11dd94b461d26f09f012750b52c968b6c15db7376835cf3f6878e9100bca54
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