Instructions to use Open-Reasoner-Zero/Open-Reasoner-Zero-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Open-Reasoner-Zero/Open-Reasoner-Zero-7B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Open-Reasoner-Zero/Open-Reasoner-Zero-7B") model = AutoModelForCausalLM.from_pretrained("Open-Reasoner-Zero/Open-Reasoner-Zero-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Open-Reasoner-Zero/Open-Reasoner-Zero-7B: direct link, hf CLI and curl.
- Browser
- Download file 7.03 MB
-
https://huggingface.co/Open-Reasoner-Zero/Open-Reasoner-Zero-7B/resolve/refs%2Fpr%2F2/tokenizer.json
- Command line
-
hf download hf://Open-Reasoner-Zero/Open-Reasoner-Zero-7B@refs/pr/2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Open-Reasoner-Zero/Open-Reasoner-Zero-7B/resolve/refs%2Fpr%2F2/tokenizer.json
7.03 MB
- Xet hash:
- fbfb5d1d988759111764e6dfea3abf13d129970336f78fd27148bb842acfd471
- Size of remote file:
- 7.03 MB
- SHA256:
- a8506e7111b80c6d8635951a02eab0f4e1a8e4e5772da83846579e97b16f61bf
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.