Instructions to use sendaljepit/daffa-ai-coder-multilang with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sendaljepit/daffa-ai-coder-multilang with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sendaljepit/daffa-ai-coder-multilang") model = AutoModelForSeq2SeqLM.from_pretrained("sendaljepit/daffa-ai-coder-multilang", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- dcef593fe1af25a48937071a37bda4b1df8459c1aa6535aa5d945a74e905e7af
- Size of remote file:
- 242 MB
- SHA256:
- 7a4960796cb7841256e07822932de0b5971e770bfd84494afaf0a0ff1aa55cb8
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