Instructions to use willieseun/Micro-Learn-Idrisi-Encoder-Decoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use willieseun/Micro-Learn-Idrisi-Encoder-Decoder with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("willieseun/Micro-Learn-Idrisi-Encoder-Decoder") model = AutoModelForSeq2SeqLM.from_pretrained("willieseun/Micro-Learn-Idrisi-Encoder-Decoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from willieseun/Micro-Learn-Idrisi-Encoder-Decoder: direct link, hf CLI and curl.
- Browser
- Download file 1.77 GB
-
https://huggingface.co/willieseun/Micro-Learn-Idrisi-Encoder-Decoder/resolve/main/model.safetensors
- Command line
-
hf download hf://willieseun/Micro-Learn-Idrisi-Encoder-Decoder/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/willieseun/Micro-Learn-Idrisi-Encoder-Decoder/resolve/main/model.safetensors
1.77 GB
- Xet hash:
- 49f86dbe2661d15721bbce53a205a947a2cba209b72f4b6e5b1186887b4d2a30
- Size of remote file:
- 1.77 GB
- SHA256:
- 8cec8a38a122fd32700134033992ff767c83ccbfb01c3a3ad07757a54e7deb73
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.