| | --- |
| | base_model: meta-llama/Llama-2-13b-hf |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: Ruckus-PyAssi-13b |
| | 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. --> |
| |
|
| | # Ruckus-PyAssi-13b |
| |
|
| | This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/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 |
| |
|
