Instructions to use code-world/google-flan-t5-small-lora-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use code-world/google-flan-t5-small-lora-ft with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-small") model = PeftModel.from_pretrained(base_model, "code-world/google-flan-t5-small-lora-ft") - Transformers
How to use code-world/google-flan-t5-small-lora-ft with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("code-world/google-flan-t5-small-lora-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from code-world/google-flan-t5-small-lora-ft: direct link, hf CLI and curl.
- Browser
- Download file 5.84 kB
-
https://huggingface.co/code-world/google-flan-t5-small-lora-ft/resolve/main/training_args.bin
- Command line
-
hf download hf://code-world/google-flan-t5-small-lora-ft/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/code-world/google-flan-t5-small-lora-ft/resolve/main/training_args.bin
5.84 kB
- Xet hash:
- 8e0543247eba5548acf9dd7ce1812b82b42088725927273682b0a8fb798d2f5b
- Size of remote file:
- 5.84 kB
- SHA256:
- e05ba337dc300eaef43d8d996a96e3721d94265241a83855a75b9460b67a8756
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