Instructions to use vertings6/7a4d843e-9dc7-414d-966b-e2e0ed141110 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use vertings6/7a4d843e-9dc7-414d-966b-e2e0ed141110 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Nous-Capybara-7B-V1") model = PeftModel.from_pretrained(base_model, "vertings6/7a4d843e-9dc7-414d-966b-e2e0ed141110") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from vertings6/7a4d843e-9dc7-414d-966b-e2e0ed141110: direct link, hf CLI and curl.
- Browser
- Download file 500 kB
-
https://huggingface.co/vertings6/7a4d843e-9dc7-414d-966b-e2e0ed141110/resolve/main/tokenizer.model
- Command line
-
hf download hf://vertings6/7a4d843e-9dc7-414d-966b-e2e0ed141110/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/vertings6/7a4d843e-9dc7-414d-966b-e2e0ed141110/resolve/main/tokenizer.model
500 kB
- Xet hash:
- 409b63d0f14ab5da7909ddcb93f85878ef0e4f19bfa91194b68ac5b45a5b6e87
- Size of remote file:
- 500 kB
- SHA256:
- 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.