Instructions to use ativilambit/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ativilambit/results with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ativilambit/results") model = AutoModelForSeq2SeqLM.from_pretrained("ativilambit/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#6 opened about 3 years ago
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Adding `safetensors` variant of this model
#5 opened about 3 years ago
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Adding `safetensors` variant of this model
#4 opened about 3 years ago
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Adding `safetensors` variant of this model
#3 opened about 3 years ago
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Adding `safetensors` variant of this model
#2 opened about 3 years ago
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Adding `safetensors` variant of this model
#1 opened about 3 years ago
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SFconvertbot