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--- |
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license: apache-2.0 |
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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: rishiraj/CatPPT-base |
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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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[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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<details><summary>See axolotl config</summary> |
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axolotl version: `0.3.0` |
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```yaml |
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base_model: rishiraj/CatPPT-base |
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model_type: MistralForCausalLM |
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tokenizer_type: LlamaTokenizer |
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is_mistral_derived_model: true |
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load_in_8bit: false |
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load_in_4bit: true |
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strict: false |
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model_config: |
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output_router_logits: true |
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datasets: |
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- path: teknium/openhermes |
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type: alpaca |
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prompt_style: chatml |
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- path: garage-bAInd/Open-Platypus |
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type: alpaca |
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prompt_style: chatml |
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- path: LDJnr/Capybara |
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type: sharegpt |
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conversation: chatml |
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- path: datasets/samantha-1.1.json |
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type: sharegpt |
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conversation: chatml |
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- path: datasets/grammarly-coedit-alpaca.jsonl |
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type: alpaca |
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prompt_style: chatml |
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- path: datasets/dolphin-coder-codegen.jsonl |
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type: alpaca_w_system.load_open_orca_chatml |
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- path: datasets/dolphin-coder-translate.jsonl |
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type: alpaca_w_system.load_open_orca_chatml |
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- path: datasets/data-evol_instruct-decontaminated-alpaca.jsonl |
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type: alpaca |
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prompt_style: chatml |
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- path: datasets/data-oss_instruct-decontaminated-alpaca.jsonl |
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type: alpaca |
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prompt_style: chatml |
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- path: jondurbin/airoboros-3.2 |
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type: sharegpt |
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conversations: chatml |
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dataset_prepared_path: last_run_prepared |
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val_set_size: 0.01 |
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output_dir: ./qlora-out-2 |
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seed: 420 |
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adapter: qlora |
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lora_model_dir: |
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sequence_len: 8192 |
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sample_packing: true |
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pad_to_sequence_len: true |
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lora_r: 32 |
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lora_alpha: 16 |
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lora_dropout: 0.05 |
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lora_target_modules: |
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lora_target_linear: true |
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lora_fan_in_fan_out: |
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lora_modules_to_save: |
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- embed_tokens |
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- lm_head |
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wandb_project: |
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wandb_entity: |
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wandb_watch: |
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wandb_name: |
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wandb_log_model: |
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gradient_accumulation_steps: 2 |
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micro_batch_size: 3 |
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num_epochs: 1.5 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.0002 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: true |
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fp16: false |
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tf32: false |
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gradient_checkpointing: true |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: true |
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loss_watchdog_threshold: 5.0 |
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loss_watchdog_patience: 3 |
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warmup_steps: 0 |
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evals_per_epoch: 20 |
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eval_table_size: |
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saves_per_epoch: 20 |
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debug: |
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deepspeed: |
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weight_decay: 0.05 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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bos_token: "<s>" |
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eos_token: "</s>" |
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unk_token: "<unk>" |
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eos_token: "<|im_end|>" |
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tokens: |
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- "<|im_start|>" |
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trust_remote_code: true |
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``` |
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</details><br> |
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# qlora-out-2 |
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This model is a fine-tuned version of [rishiraj/CatPPT-base](https://huggingface.co./rishiraj/CatPPT-base) on multiple datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4258 |
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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: 3 |
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- eval_batch_size: 3 |
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- seed: 420 |
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- distributed_type: multi-GPU |
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- num_devices: 3 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 18 |
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- total_eval_batch_size: 9 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- num_epochs: 1.5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.7691 | 0.0 | 1 | 0.7027 | |
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| 0.5556 | 0.05 | 135 | 0.5808 | |
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| 0.597 | 0.1 | 270 | 0.5488 | |
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| 0.5979 | 0.15 | 405 | 0.5277 | |
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| 0.4693 | 0.2 | 540 | 0.5108 | |
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| 0.5123 | 0.25 | 675 | 0.4978 | |
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| 0.4394 | 0.3 | 810 | 0.4883 | |
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| 0.46 | 0.35 | 945 | 0.4802 | |
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| 0.4472 | 0.4 | 1080 | 0.4748 | |
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| 0.47 | 0.45 | 1215 | 0.4687 | |
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| 0.4249 | 0.5 | 1350 | 0.4637 | |
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| 0.4823 | 0.55 | 1485 | 0.4599 | |
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| 0.4209 | 0.6 | 1620 | 0.4555 | |
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| 0.4909 | 0.65 | 1755 | 0.4517 | |
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| 0.4663 | 0.7 | 1890 | 0.4470 | |
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| 0.4215 | 0.75 | 2025 | 0.4437 | |
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| 0.4267 | 0.8 | 2160 | 0.4398 | |
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| 0.4109 | 0.85 | 2295 | 0.4364 | |
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| 0.4099 | 0.9 | 2430 | 0.4331 | |
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| 0.447 | 0.95 | 2565 | 0.4298 | |
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| 0.4412 | 1.0 | 2700 | 0.4272 | |
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| 0.3838 | 1.03 | 2835 | 0.4287 | |
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| 0.4262 | 1.08 | 2970 | 0.4274 | |
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| 0.3889 | 1.13 | 3105 | 0.4263 | |
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| 0.3114 | 1.18 | 3240 | 0.4255 | |
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| 0.3685 | 1.23 | 3375 | 0.4256 | |
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| 0.392 | 1.28 | 3510 | 0.4253 | |
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| 0.3751 | 1.33 | 3645 | 0.4255 | |
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| 0.3756 | 1.39 | 3780 | 0.4256 | |
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| 0.3108 | 1.44 | 3915 | 0.4258 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.1+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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## Training procedure |
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The following `bitsandbytes` quantization config was used during training: |
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- quant_method: bitsandbytes |
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- load_in_8bit: False |
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- load_in_4bit: True |
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- llm_int8_threshold: 6.0 |
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- llm_int8_skip_modules: None |
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- llm_int8_enable_fp32_cpu_offload: False |
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- llm_int8_has_fp16_weight: False |
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- bnb_4bit_quant_type: nf4 |
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- bnb_4bit_use_double_quant: True |
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- bnb_4bit_compute_dtype: bfloat16 |
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### Framework versions |
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- PEFT 0.6.0 |
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