Instructions to use seyonec/checkpoint-50000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use seyonec/checkpoint-50000 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="seyonec/checkpoint-50000")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("seyonec/checkpoint-50000") model = AutoModelForMaskedLM.from_pretrained("seyonec/checkpoint-50000", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from seyonec/checkpoint-50000: direct link, hf CLI and curl.
- Browser
- Download file 668 MB
-
https://huggingface.co/seyonec/checkpoint-50000/resolve/main/optimizer.pt
- Command line
-
hf download hf://seyonec/checkpoint-50000/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/seyonec/checkpoint-50000/resolve/main/optimizer.pt
668 MB
- Xet hash:
- 158e90fabb702d54c8afa87b37b68005bdce24068a23dbb033b5c91a1161c780
- Size of remote file:
- 668 MB
- SHA256:
- 3e5dfb414d5ea1f10592acbbca10a8af58d06b82c13d8976cbddeb5b19ade481
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.