Instructions to use OmAlve/Topic-Tagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use OmAlve/Topic-Tagger with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/gemma-2b") model = PeftModel.from_pretrained(base_model, "OmAlve/Topic-Tagger") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from OmAlve/Topic-Tagger: direct link, hf CLI and curl.
- Browser
- Download file 17.5 MB
-
https://huggingface.co/OmAlve/Topic-Tagger/resolve/main/tokenizer.json
- Command line
-
hf download hf://OmAlve/Topic-Tagger/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/OmAlve/Topic-Tagger/resolve/main/tokenizer.json
17.5 MB
- Xet hash:
- 2fe6a5269312eafc0dd82845e69a776ce6b9bc0a9bceca38b245377f7ea519ca
- Size of remote file:
- 17.5 MB
- SHA256:
- 0adfe100f7aaea5ab4011f4643c4359be2df636f514cd0574085e7a633874c19
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.