Instructions to use igorktech/hibial-bert-i3-mlm-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use igorktech/hibial-bert-i3-mlm-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="igorktech/hibial-bert-i3-mlm-v0.1", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("igorktech/hibial-bert-i3-mlm-v0.1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| base_model: /content/hier-bert-pytorch/data/hibial-model | |
| tags: | |
| - generated_from_trainer | |
| model-index: | |
| - name: hibial-bert-i3-mlm | |
| results: [] | |
| pipeline_tag: fill-mask | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| # hibial-bert-i3-mlm | |
| This model is a fine-tuned version of [/content/hier-bert-pytorch/data/hibial-model](https://huggingface.co//content/hier-bert-pytorch/data/hibial-model) on an unknown dataset. | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - learning_rate: 0.001 | |
| - train_batch_size: 64 | |
| - eval_batch_size: 4 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 4 | |
| - total_train_batch_size: 256 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - lr_scheduler_warmup_ratio: 0.5 | |
| - training_steps: 5000 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.33.2 | |
| - Pytorch 2.0.1+cu118 | |
| - Datasets 2.14.5 | |
| - Tokenizers 0.13.3 |