Instructions to use TypicaAI/magbert-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TypicaAI/magbert-lm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="TypicaAI/magbert-lm")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("TypicaAI/magbert-lm") model = AutoModelForMaskedLM.from_pretrained("TypicaAI/magbert-lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download log_history.json from TypicaAI/magbert-lm: direct link, hf CLI and curl.
- Browser
- Download file 500 Bytes
-
https://huggingface.co/TypicaAI/magbert-lm/resolve/3e40153dc0c61ab12ded4ade63e0e8bda8b8a807/log_history.json
- Command line
-
hf download hf://TypicaAI/magbert-lm@3e40153dc0c61ab12ded4ade63e0e8bda8b8a807/log_history.json
-
curl -L -o log_history.json https://huggingface.co/TypicaAI/magbert-lm/resolve/3e40153dc0c61ab12ded4ade63e0e8bda8b8a807/log_history.json
500 Bytes
| [ | |
| { | |
| "loss": 2.2677119140625, | |
| "learning_rate": 3.433583959899749e-05, | |
| "epoch": 0.9398496240601504, | |
| "total_flos": 2448414782266752, | |
| "step": 500 | |
| }, | |
| { | |
| "loss": 2.0084296875, | |
| "learning_rate": 1.8671679197994987e-05, | |
| "epoch": 1.8796992481203008, | |
| "total_flos": 4915568408340096, | |
| "step": 1000 | |
| }, | |
| { | |
| "loss": 1.92304296875, | |
| "learning_rate": 3.007518796992481e-06, | |
| "epoch": 2.819548872180451, | |
| "total_flos": 7378600338610176, | |
| "step": 1500 | |
| } | |
| ] |