Instructions to use buming/peft-starcoder-lora-a100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use buming/peft-starcoder-lora-a100 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigcode/starcoderbase-1b") model = PeftModel.from_pretrained(base_model, "buming/peft-starcoder-lora-a100") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from buming/peft-starcoder-lora-a100: direct link, hf CLI and curl.
- Browser
- Download file 4.86 kB
-
https://huggingface.co/buming/peft-starcoder-lora-a100/resolve/main/training_args.bin
- Command line
-
hf download hf://buming/peft-starcoder-lora-a100/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/buming/peft-starcoder-lora-a100/resolve/main/training_args.bin
4.86 kB
- Xet hash:
- a79c332c29f2879e750275a27dfa52128528b84774512ff0530645322c163a0c
- Size of remote file:
- 4.86 kB
- SHA256:
- 6cdb316cac23a37d1c4a2b8835c4da20b9b16c52389a08c93282d50ba23e8b81
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