EarlyCheckpoint is the first saved checkpoint from our training run, captured at the very beginning of training. It serves as a baseline for comparing training progress.
This model represents the initial state of training and is useful for ablation studies and understanding training dynamics.
1from transformers import AutoModel, AutoTokenizer
2
3model = AutoModel.from_pretrained("EarlyCheckpoint-v1")
4tokenizer = AutoTokenizer.from_pretrained("EarlyCheckpoint-v1")
This model is licensed under the
Apache-2.0 License.
Open an issue on our GitHub for questions.
