Instructions to use dusersad12/NexusLM-BestCheckpoint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/NexusLM-BestCheckpoint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="dusersad12/NexusLM-BestCheckpoint")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("dusersad12/NexusLM-BestCheckpoint") model = AutoModel.from_pretrained("dusersad12/NexusLM-BestCheckpoint", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dusersad12/NexusLM-BestCheckpoint: direct link, hf CLI and curl.
- Browser
- Download file 1.02 kB
-
https://huggingface.co/dusersad12/NexusLM-BestCheckpoint/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/NexusLM-BestCheckpoint/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/NexusLM-BestCheckpoint/resolve/main/pytorch_model.bin
1.02 kB
- Xet hash:
- 8d1387b8d303f598add509417371c19a2d5790820cd9460d485ad1a0bfd60ab7
- Size of remote file:
- 1.02 kB
- SHA256:
- 89630b0357ca2cab2ccc6d5d864a9b801b78a35f03adfca038e681cef200e1c2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.