Instructions to use rahkrish1/peft-starcoder-lora-a100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rahkrish1/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, "rahkrish1/peft-starcoder-lora-a100") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rahkrish1/peft-starcoder-lora-a100: direct link, hf CLI and curl.
- Browser
- Download file 5.37 kB
-
https://huggingface.co/rahkrish1/peft-starcoder-lora-a100/resolve/c2cf2b9f6e433582d3c87a5aa73c45e2a8f74d71/training_args.bin
- Command line
-
hf download hf://rahkrish1/peft-starcoder-lora-a100@c2cf2b9f6e433582d3c87a5aa73c45e2a8f74d71/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rahkrish1/peft-starcoder-lora-a100/resolve/c2cf2b9f6e433582d3c87a5aa73c45e2a8f74d71/training_args.bin
5.37 kB
- Xet hash:
- f04e9e233eeabe99afab562e220559d7cad12ddc0821ab7b538eaa2433e86eb2
- Size of remote file:
- 5.37 kB
- SHA256:
- 705ab4268fb493ca2a098e4e0ed753ae3f0804d61a3122760d0ffcdf6ee48f76
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