Instructions to use NotoriousH2/outputs_solar_10.7b_v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use NotoriousH2/outputs_solar_10.7b_v1.0 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("upstage/SOLAR-10.7B-v1.0") model = PeftModel.from_pretrained(base_model, "NotoriousH2/outputs_solar_10.7b_v1.0") - Notebooks
- Google Colab
- Kaggle
outputs_solar_10.7b_v1.0
This model is a fine-tuned version of upstage/SOLAR-10.7B-v1.0 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 10
- mixed_precision_training: Native AMP
Training results
Framework versions
- PEFT 0.7.2.dev0
- Transformers 4.37.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
- Downloads last month
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Model tree for NotoriousH2/outputs_solar_10.7b_v1.0
Base model
upstage/SOLAR-10.7B-v1.0