Instructions to use shouray/qlora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shouray/qlora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TheBloke/Llama-2-13B-chat-GPTQ") model = PeftModel.from_pretrained(base_model, "shouray/qlora") - Notebooks
- Google Colab
- Kaggle
shouray/Condition-Model
Browse files- README.md +82 -0
- adapter_config.json +31 -0
- adapter_model.safetensors +3 -0
- runs/Jun14_15-03-14_6574e26d2cdf/events.out.tfevents.1718377616.6574e26d2cdf.1380.0 +3 -0
- runs/Jun17_23-57-11_3a79ca44463a/events.out.tfevents.1718668633.3a79ca44463a.318.1 +3 -0
- runs/Jun17_23-58-31_3a79ca44463a/events.out.tfevents.1718668712.3a79ca44463a.318.2 +3 -0
- runs/Jun18_00-00-11_3a79ca44463a/events.out.tfevents.1718668812.3a79ca44463a.318.3 +3 -0
- runs/Jun18_00-00-28_3a79ca44463a/events.out.tfevents.1718668829.3a79ca44463a.318.4 +3 -0
- runs/Jun18_00-02-31_3a79ca44463a/events.out.tfevents.1718668952.3a79ca44463a.318.5 +3 -0
- runs/Jun18_00-03-20_3a79ca44463a/events.out.tfevents.1718669000.3a79ca44463a.318.6 +3 -0
- runs/Jun18_00-06-59_3a79ca44463a/events.out.tfevents.1718669220.3a79ca44463a.318.7 +3 -0
- runs/Jun18_20-00-42_cc2260668183/events.out.tfevents.1718740843.cc2260668183.461.1 +3 -0
- runs/Jun18_20-04-17_cc2260668183/events.out.tfevents.1718741058.cc2260668183.461.2 +3 -0
- runs/Jun18_20-05-29_cc2260668183/events.out.tfevents.1718741129.cc2260668183.461.3 +3 -0
- runs/Jun18_20-06-24_cc2260668183/events.out.tfevents.1718741185.cc2260668183.461.4 +3 -0
- runs/Jun18_20-10-43_cc2260668183/events.out.tfevents.1718741444.cc2260668183.461.5 +3 -0
- runs/Jun18_20-14-05_cc2260668183/events.out.tfevents.1718741645.cc2260668183.461.6 +3 -0
- runs/Jun18_20-14-14_cc2260668183/events.out.tfevents.1718741655.cc2260668183.461.7 +3 -0
- runs/Jun18_20-14-20_cc2260668183/events.out.tfevents.1718741660.cc2260668183.461.8 +3 -0
- runs/Jun18_20-15-38_cc2260668183/events.out.tfevents.1718741738.cc2260668183.461.9 +3 -0
- training_args.bin +3 -0
README.md
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---
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license: llama2
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library_name: peft
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tags:
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- generated_from_trainer
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base_model: TheBloke/Llama-2-13B-chat-GPTQ
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model-index:
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- name: qlora
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# qlora
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This model is a fine-tuned version of [TheBloke/Llama-2-13B-chat-GPTQ](https://huggingface.co/TheBloke/Llama-2-13B-chat-GPTQ) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2281
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0002
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 16
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 2
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- training_steps: 30
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss |
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|:-------------:|:-----:|:----:|:---------------:|
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| 1.7256 | 1.0 | 1 | 2.3492 |
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| 0.8422 | 2.0 | 3 | 2.0594 |
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| 0.7278 | 3.0 | 5 | 1.6949 |
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| 1.2299 | 4.0 | 6 | 1.5504 |
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| 1.1219 | 5.0 | 7 | 1.4207 |
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| 0.4884 | 6.0 | 9 | 1.2156 |
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| 0.4229 | 7.0 | 11 | 0.9934 |
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| 0.7082 | 8.0 | 12 | 0.8837 |
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| 0.6263 | 9.0 | 13 | 0.7754 |
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| 0.2502 | 10.0 | 15 | 0.5958 |
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| 0.1915 | 11.0 | 17 | 0.4347 |
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| 0.2841 | 12.0 | 18 | 0.3766 |
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| 0.2395 | 13.0 | 19 | 0.3339 |
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| 0.0959 | 14.0 | 21 | 0.2914 |
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| 0.0808 | 15.0 | 23 | 0.2631 |
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| 0.1391 | 16.0 | 24 | 0.2533 |
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| 0.13 | 17.0 | 25 | 0.2434 |
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| 0.0589 | 18.0 | 27 | 0.2357 |
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| 0.0558 | 19.0 | 29 | 0.2298 |
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| 0.1076 | 20.0 | 30 | 0.2281 |
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### Framework versions
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- PEFT 0.11.1
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- Transformers 4.41.2
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- Pytorch 2.1.0+cu121
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- Datasets 2.20.0
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- Tokenizers 0.19.1
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adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "TheBloke/Llama-2-13B-chat-GPTQ",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"r": 8,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"q_proj",
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"o_proj",
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"v_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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training_args.bin
ADDED
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@@ -0,0 +1,3 @@
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| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:c87801c6747a4cd159adbfe4f2017b4086ce356a7f6327f2e2eb3f5e8fd66427
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| 3 |
+
size 5112
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