Instructions to use currentlyexhausted/lite-llm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use currentlyexhausted/lite-llm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("currentlyexhausted/lite-llm") model = AutoModelForSeq2SeqLM.from_pretrained("currentlyexhausted/lite-llm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload ./ with huggingface_hub
8ce2074 -
Upload ./ with huggingface_hub
f3558c7 -
Upload ./ with huggingface_hub
bc26dd8
-
Upload folder using huggingface_hub
006d237
-
Upload folder using huggingface_hub
8630535 -
Upload folder using huggingface_hub
c0ca4ca -
Upload folder using huggingface_hub
82b7527 -
Upload folder using huggingface_hub
ea845c3 -
Upload folder using huggingface_hub
83c215d -
Upload folder using huggingface_hub
c3c8d08
-
Upload folder using huggingface_hub
834ef33 -
Upload folder using huggingface_hub
576d880 -
Upload folder using huggingface_hub
5cd0e3d -
initial commit
9dfbf9b