Translation
Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use iRpro16/model_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iRpro16/model_trainer with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="iRpro16/model_trainer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("iRpro16/model_trainer") model = AutoModelForSeq2SeqLM.from_pretrained("iRpro16/model_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from iRpro16/model_trainer: direct link, hf CLI and curl.
- Browser
- Download file 1.14 kB
-
https://huggingface.co/iRpro16/model_trainer/resolve/main/README.md
- Command line
-
hf download hf://iRpro16/model_trainer/README.md
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curl -L -o README.md https://huggingface.co/iRpro16/model_trainer/resolve/main/README.md
1.14 kB
| license: apache-2.0 | |
| base_model: t5-small | |
| tags: | |
| - translation | |
| - generated_from_trainer | |
| model-index: | |
| - name: model_trainer | |
| results: [] | |
| <!-- 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. --> | |
| # model_trainer | |
| This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) 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: 32 | |
| - eval_batch_size: 32 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 4 | |
| - total_train_batch_size: 128 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: linear | |
| - num_epochs: 2 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.41.2 | |
| - Pytorch 2.0.1 | |
| - Datasets 2.20.0 | |
| - Tokenizers 0.19.1 | |