Instructions to use lchen915/sft_openassistant-guanaco_temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lchen915/sft_openassistant-guanaco_temp with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("facebook/opt-350m") model = PeftModel.from_pretrained(base_model, "lchen915/sft_openassistant-guanaco_temp") - Notebooks
- Google Colab
- Kaggle
sft_openassistant-guanaco_temp
This model is a fine-tuned version of facebook/opt-350m 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: 8.81e-07
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
Training results
Framework versions
- PEFT 0.13.0
- Transformers 4.45.0
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.20.0
- Downloads last month
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Model tree for lchen915/sft_openassistant-guanaco_temp
Base model
facebook/opt-350m