Instructions to use baby-dev/tttt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use baby-dev/tttt with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("katuni4ka/tiny-random-codegen2") model = PeftModel.from_pretrained(base_model, "baby-dev/tttt") - Notebooks
- Google Colab
- Kaggle
root/workspace/outputs/21/tttt
This model is a fine-tuned version of katuni4ka/tiny-random-codegen2 on the /root/workspace/input_data/e42a4124494711a3_train_data.json dataset. It achieves the following results on the evaluation set:
- Loss: 10.7222
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Framework versions
- PEFT 0.14.0
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
katuni4ka/tiny-random-codegen2