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 tokenizer.json from build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8: direct link, hf CLI and curl.
- Browser
- Download file 9.89 MB
-
https://huggingface.co/build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8/resolve/main/tokenizer.json
- Command line
-
hf download hf://build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/build-small-hackathon/jawbreaker-minicpm5-1b-lora-v8/resolve/main/tokenizer.json
9.89 MB
File too large to display, you can check the raw version instead.