Instructions to use ManyaGupta/bloom_ts2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ManyaGupta/bloom_ts2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("bigscience/bloomz-560m") model = PeftModel.from_pretrained(base_model, "ManyaGupta/bloom_ts2") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ManyaGupta/bloom_ts2: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/ManyaGupta/bloom_ts2/resolve/main/training_args.bin
- Command line
-
hf download hf://ManyaGupta/bloom_ts2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ManyaGupta/bloom_ts2/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- f59a09ce6913e4bdd055e5f94b0c1e069ff9560a524c4ee997f6a7314e0ac901
- Size of remote file:
- 5.43 kB
- SHA256:
- 08c24f030ffcfc0aec6f075714fa7262d52e4b6a5d74d78cc649887558d1baa7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.