Instructions to use dusersad12/NimbusLM-ReleaseRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/NimbusLM-ReleaseRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/NimbusLM-ReleaseRepo")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/NimbusLM-ReleaseRepo") model = AutoModel.from_pretrained("dusersad12/NimbusLM-ReleaseRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dusersad12/NimbusLM-ReleaseRepo: direct link, hf CLI and curl.
- Browser
- Download file 86 Bytes
-
https://huggingface.co/dusersad12/NimbusLM-ReleaseRepo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/NimbusLM-ReleaseRepo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/NimbusLM-ReleaseRepo/resolve/main/pytorch_model.bin
86 Bytes
- Xet hash:
- 8d9acc9a733da9999b5923b28bb546da47968315bb4ea277e2434ca6857a05f9
- Size of remote file:
- 86 Bytes
- SHA256:
- c01f1db397e465ff91630e3eee31d00e3ee9ff308df29ece301e65228fb1c30e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.