PEFT
Safetensors
build-small-hackathon
openbmb
minicpm
minicpm5
lora
scam-defense
tiny-titan
well-tuned
Instructions to use build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM5-1B") model = PeftModel.from_pretrained(base_model, "build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8: direct link, hf CLI and curl.
- Browser
- Download file 5.91 kB
-
https://huggingface.co/build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8/resolve/main/training_args.bin
- Command line
-
hf download hf://build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8/resolve/main/training_args.bin
5.91 kB
- Xet hash:
- 1718912c4685b3ee956fed496d6e430234396bd1368ea6e02b6853900805c450
- Size of remote file:
- 5.91 kB
- SHA256:
- 21f7168615bc8c271c9323048301d8b00c7b5a8e22127882368b665f91b92c5d
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