Instructions to use Rizald95/code2api-train-v1-experiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Rizald95/code2api-train-v1-experiment with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/phi-3.5-mini-instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "Rizald95/code2api-train-v1-experiment") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Rizald95/code2api-train-v1-experiment: direct link, hf CLI and curl.
- Browser
- Download file 1.84 MB
-
https://huggingface.co/Rizald95/code2api-train-v1-experiment/resolve/main/tokenizer.json
- Command line
-
hf download hf://Rizald95/code2api-train-v1-experiment/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Rizald95/code2api-train-v1-experiment/resolve/main/tokenizer.json
1.84 MB
File too large to display, you can check the raw version instead.