Instructions to use rushichavda/bloom_1b_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use rushichavda/bloom_1b_lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigscience/bloom-1b7") model = PeftModel.from_pretrained(base_model, "rushichavda/bloom_1b_lora") - Notebooks
- Google Colab
- Kaggle
Download adapter_model.bin from rushichavda/bloom_1b_lora: direct link, hf CLI and curl.
- Browser
- Download file 6.31 MB
-
https://huggingface.co/rushichavda/bloom_1b_lora/resolve/main/adapter_model.bin
- Command line
-
hf download hf://rushichavda/bloom_1b_lora/adapter_model.bin
-
curl -L -o adapter_model.bin https://huggingface.co/rushichavda/bloom_1b_lora/resolve/main/adapter_model.bin
6.31 MB
- Xet hash:
- b510550eec942c16394adcd4f530dbcb9381cebb5164d9401710b408bed9886d
- Size of remote file:
- 6.31 MB
- SHA256:
- f7cbf6272e6c757d640cdf40a22a6037699018ae4102b2fad846e4ed1198c5c0
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