Instructions to use ani-kavle/EvolCodeLlama-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ani-kavle/EvolCodeLlama-7b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "ani-kavle/EvolCodeLlama-7b") - Notebooks
- Google Colab
- Kaggle
| base_model: codellama/CodeLlama-7b-hf | |
| library_name: peft | |
| license: llama2 | |
| tags: | |
| - axolotl | |
| - generated_from_trainer | |
| model-index: | |
| - name: EvolCodeLlama-7b | |
| 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. --> | |
| [<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl) | |
| <details><summary>See axolotl config</summary> | |
| axolotl version: `0.4.1` | |
| ```yaml | |
| base_model: codellama/CodeLlama-7b-hf | |
| base_model_config: codellama/CodeLlama-7b-hf | |
| model_type: LlamaForCausalLM | |
| tokenizer_type: LlamaTokenizer | |
| is_llama_derived_model: true | |
| hub_model_id: EvolCodeLlama-7b | |
| load_in_8bit: false | |
| load_in_4bit: true | |
| strict: false | |
| datasets: | |
| - path: mlabonne/Evol-Instruct-Python-1k | |
| type: alpaca | |
| dataset_prepared_path: last_run_prepared | |
| val_set_size: 0.02 | |
| output_dir: ./qlora-out | |
| adapter: qlora | |
| lora_model_dir: | |
| sequence_len: 2048 | |
| sample_packing: true | |
| lora_r: 32 | |
| lora_alpha: 16 | |
| lora_dropout: 0.05 | |
| lora_target_modules: | |
| lora_target_linear: true | |
| lora_fan_in_fan_out: | |
| wandb_project: axolotl | |
| wandb_entity: | |
| wandb_watch: | |
| wandb_run_id: | |
| wandb_log_model: | |
| gradient_accumulation_steps: 4 | |
| micro_batch_size: 2 | |
| num_epochs: 3 | |
| optimizer: paged_adamw_32bit | |
| lr_scheduler: cosine | |
| learning_rate: 0.0002 | |
| train_on_inputs: false | |
| group_by_length: false | |
| bf16: true | |
| fp16: false | |
| tf32: false | |
| gradient_checkpointing: true | |
| early_stopping_patience: | |
| resume_from_checkpoint: | |
| local_rank: | |
| logging_steps: 1 | |
| xformers_attention: | |
| flash_attention: true | |
| warmup_steps: 100 | |
| eval_steps: 0.01 | |
| save_strategy: epoch | |
| save_steps: | |
| debug: | |
| deepspeed: | |
| weight_decay: 0.0 | |
| fsdp: | |
| fsdp_config: | |
| special_tokens: | |
| bos_token: "<s>" | |
| eos_token: "</s>" | |
| unk_token: "<unk>" | |
| ``` | |
| </details><br> | |
| # EvolCodeLlama-7b | |
| This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on the None dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.3796 | |
| ## 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: 0.0002 | |
| - train_batch_size: 2 | |
| - eval_batch_size: 2 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 4 | |
| - total_train_batch_size: 8 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: cosine | |
| - lr_scheduler_warmup_steps: 100 | |
| - num_epochs: 3 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:------:|:----:|:---------------:| | |
| | 0.4828 | 0.0086 | 1 | 0.4975 | | |
| | 0.4056 | 0.0343 | 4 | 0.4976 | | |
| | 0.5046 | 0.0685 | 8 | 0.4973 | | |
| | 0.3969 | 0.1028 | 12 | 0.4966 | | |
| | 0.3404 | 0.1370 | 16 | 0.4947 | | |
| | 0.4645 | 0.1713 | 20 | 0.4896 | | |
| | 0.2892 | 0.2056 | 24 | 0.4789 | | |
| | 0.2616 | 0.2398 | 28 | 0.4616 | | |
| | 0.2586 | 0.2741 | 32 | 0.4430 | | |
| | 0.3147 | 0.3084 | 36 | 0.4267 | | |
| | 0.3686 | 0.3426 | 40 | 0.4158 | | |
| | 0.2935 | 0.3769 | 44 | 0.4084 | | |
| | 0.2419 | 0.4111 | 48 | 0.4026 | | |
| | 0.2791 | 0.4454 | 52 | 0.3970 | | |
| | 0.2381 | 0.4797 | 56 | 0.3922 | | |
| | 0.2407 | 0.5139 | 60 | 0.3888 | | |
| | 0.2686 | 0.5482 | 64 | 0.3872 | | |
| | 0.3673 | 0.5824 | 68 | 0.3880 | | |
| | 0.2665 | 0.6167 | 72 | 0.3848 | | |
| | 0.3259 | 0.6510 | 76 | 0.3830 | | |
| | 0.236 | 0.6852 | 80 | 0.3801 | | |
| | 0.2301 | 0.7195 | 84 | 0.3786 | | |
| | 0.3573 | 0.7537 | 88 | 0.3766 | | |
| | 0.2409 | 0.7880 | 92 | 0.3745 | | |
| | 0.3192 | 0.8223 | 96 | 0.3744 | | |
| | 0.2652 | 0.8565 | 100 | 0.3720 | | |
| | 0.2341 | 0.8908 | 104 | 0.3712 | | |
| | 0.3651 | 0.9251 | 108 | 0.3709 | | |
| | 0.1667 | 0.9593 | 112 | 0.3714 | | |
| | 0.2755 | 0.9936 | 116 | 0.3699 | | |
| | 0.2906 | 1.0254 | 120 | 0.3712 | | |
| | 0.2079 | 1.0593 | 124 | 0.3708 | | |
| | 0.3429 | 1.0932 | 128 | 0.3708 | | |
| | 0.3296 | 1.1271 | 132 | 0.3721 | | |
| | 0.2231 | 1.1610 | 136 | 0.3707 | | |
| | 0.2098 | 1.1949 | 140 | 0.3686 | | |
| | 0.2918 | 1.2288 | 144 | 0.3711 | | |
| | 0.3803 | 1.2627 | 148 | 0.3676 | | |
| | 0.2619 | 1.2966 | 152 | 0.3662 | | |
| | 0.2261 | 1.3305 | 156 | 0.3679 | | |
| | 0.1954 | 1.3644 | 160 | 0.3689 | | |
| | 0.2183 | 1.3983 | 164 | 0.3677 | | |
| | 0.2459 | 1.4322 | 168 | 0.3674 | | |
| | 0.1979 | 1.4661 | 172 | 0.3669 | | |
| | 0.2175 | 1.5 | 176 | 0.3653 | | |
| | 0.26 | 1.5339 | 180 | 0.3652 | | |
| | 0.2195 | 1.5678 | 184 | 0.3645 | | |
| | 0.3344 | 1.6017 | 188 | 0.3645 | | |
| | 0.1769 | 1.6356 | 192 | 0.3643 | | |
| | 0.1829 | 1.6695 | 196 | 0.3639 | | |
| | 0.2343 | 1.7034 | 200 | 0.3649 | | |
| | 0.2568 | 1.7373 | 204 | 0.3650 | | |
| | 0.1749 | 1.7712 | 208 | 0.3640 | | |
| | 0.2118 | 1.8051 | 212 | 0.3628 | | |
| | 0.2252 | 1.8390 | 216 | 0.3611 | | |
| | 0.2301 | 1.8729 | 220 | 0.3602 | | |
| | 0.1884 | 1.9068 | 224 | 0.3602 | | |
| | 0.2023 | 1.9407 | 228 | 0.3600 | | |
| | 0.2428 | 1.9746 | 232 | 0.3587 | | |
| | 0.2413 | 2.0064 | 236 | 0.3583 | | |
| | 0.2015 | 2.0407 | 240 | 0.3620 | | |
| | 0.2131 | 2.0749 | 244 | 0.3728 | | |
| | 0.1768 | 2.1092 | 248 | 0.3834 | | |
| | 0.1615 | 2.1435 | 252 | 0.3810 | | |
| | 0.1598 | 2.1777 | 256 | 0.3775 | | |
| | 0.171 | 2.2120 | 260 | 0.3763 | | |
| | 0.1973 | 2.2463 | 264 | 0.3759 | | |
| | 0.1407 | 2.2805 | 268 | 0.3758 | | |
| | 0.1998 | 2.3148 | 272 | 0.3771 | | |
| | 0.1267 | 2.3490 | 276 | 0.3773 | | |
| | 0.1526 | 2.3833 | 280 | 0.3782 | | |
| | 0.1547 | 2.4176 | 284 | 0.3776 | | |
| | 0.1439 | 2.4518 | 288 | 0.3768 | | |
| | 0.1565 | 2.4861 | 292 | 0.3757 | | |
| | 0.2113 | 2.5203 | 296 | 0.3767 | | |
| | 0.1768 | 2.5546 | 300 | 0.3776 | | |
| | 0.2366 | 2.5889 | 304 | 0.3792 | | |
| | 0.1397 | 2.6231 | 308 | 0.3801 | | |
| | 0.3598 | 2.6574 | 312 | 0.3805 | | |
| | 0.1296 | 2.6916 | 316 | 0.3803 | | |
| | 0.1344 | 2.7259 | 320 | 0.3805 | | |
| | 0.2095 | 2.7602 | 324 | 0.3804 | | |
| | 0.1646 | 2.7944 | 328 | 0.3800 | | |
| | 0.1749 | 2.8287 | 332 | 0.3799 | | |
| | 0.1597 | 2.8630 | 336 | 0.3800 | | |
| | 0.1602 | 2.8972 | 340 | 0.3799 | | |
| | 0.1786 | 2.9315 | 344 | 0.3797 | | |
| | 0.1692 | 2.9657 | 348 | 0.3797 | | |
| | 0.1887 | 3.0 | 352 | 0.3796 | | |
| ### Framework versions | |
| - PEFT 0.13.0 | |
| - Transformers 4.45.0 | |
| - Pytorch 2.3.1+cu121 | |
| - Datasets 2.21.0 | |
| - Tokenizers 0.20.0 |