Instructions to use LLM-CLEM/Gamia-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LLM-CLEM/Gamia-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("LLM-CLEM/Gamia-v1") model = AutoModelForSeq2SeqLM.from_pretrained("LLM-CLEM/Gamia-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d0763c91a4a35ad0ed8af95dd37803c3a80e97986e2a432678cc829c7f2f7a2d
- Size of remote file:
- 5.5 kB
- SHA256:
- 620148ed82e33d118a232eb16bf90c8c671f0d4f21051db4bf4568971294d325
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