Instructions to use SangMoone/results_1027_easy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SangMoone/results_1027_easy with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b-it") model = PeftModel.from_pretrained(base_model, "SangMoone/results_1027_easy") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from SangMoone/results_1027_easy: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/SangMoone/results_1027_easy/resolve/main/tokenizer.json
- Command line
-
hf download hf://SangMoone/results_1027_easy/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SangMoone/results_1027_easy/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 3aa489eeb549331c3051cf38d5e566bc297111a20cff42db5c9c15bdc6f7a6c0
- Size of remote file:
- 34.4 MB
- SHA256:
- 9857ab6cf9d3e3d8e322173736e23362ef9eab7cf89472e59dc362d86f9e067c
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