Ruckus-PyAssi-13b
This model is a fine-tuned version of meta-llama/Llama-2-13b-hf on a 10 000 examples from flytech/llama-python-codes-30k dataset.
Model description
Model trained in 4-bit architecture using SFT (Supervised Fine Tuning) and LoRA (Low-Rank Adaptation) methods, fine-tuning further is possible.
Intended uses & limitations
Code-generation, but as like all Ruckus models
- Created to serve as an executional layer
- Rich in Python codes and instructional tasks
- Specially formatted for chat (see inference)
Training procedure
Model was being trained for 13 hours of A6000 single 48GB vRAM GPU
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 32
- eval_batch_size: 32 * 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 5
Inference
- Make sure to format your prompt: [INST]This is my prompt[/INST]
[INST]Ruckus, open google[/INST]
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1