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README.md CHANGED
@@ -1,3 +1,144 @@
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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ base_model: UnfilteredAI/NSFW-3B
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+ library_name: peft
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: outputs/32r
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+ results: []
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+ ---
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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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+
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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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+
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+ axolotl version: `0.4.1`
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+ ```yaml
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+ base_model: UnfilteredAI/NSFW-3B
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+ model_type: AutoModelForCausalLM
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+ tokenizer_type: AutoTokenizer
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+
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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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+
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+ datasets:
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+ - path: Fischerboot/freedom-rp-alpaca-shortend
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+ type: alpaca
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+ - path: Fischerboot/mongotom-40k-alpaca
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+ type: alpaca
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+ - path: TokenBender/roleplay_alpaca
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+ type: alpaca
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+ ds_type: parquet
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+ dataset_prepared_path:
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+ val_set_size: 0.05
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+ output_dir: ./outputs/32r
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+
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+ adapter: qlora
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+ lora_model_dir:
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+
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+ sequence_len: 4096
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+ sample_packing: true
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+ eval_sample_packing: false
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+ pad_to_sequence_len: true
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+
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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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+
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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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+
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+ gradient_accumulation_steps: 4
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+ micro_batch_size: 2
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+ num_epochs: 2
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+ optimizer: paged_adamw_32bit
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+ lr_scheduler: cosine
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+ learning_rate: 0.0002
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+
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+ train_on_inputs: false
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+ group_by_length: false
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+ bf16: auto
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+ fp16:
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+ tf32: false
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+
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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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+
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+ warmup_steps: 10
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+ evals_per_epoch: 1
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+ saves_per_epoch: 1
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+ debug:
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+ deepspeed:
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+ weight_decay: 0.0
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+ fsdp:
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+ fsdp_config:
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+ special_tokens:
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+ trust_remote_code: true
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+ ```
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+
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+ </details><br>
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+
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+ # outputs/32r
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+
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+ This model is a fine-tuned version of [UnfilteredAI/NSFW-3B](https://huggingface.co/UnfilteredAI/NSFW-3B) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 2.1202
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 8
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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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+ - lr_scheduler_warmup_steps: 10
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+ - num_epochs: 2
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:------:|:----:|:---------------:|
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+ | 8.0268 | 0.0032 | 1 | 3.2872 |
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+ | 2.2591 | 1.0 | 314 | 2.1557 |
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+ | 2.045 | 1.9753 | 628 | 2.1202 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.11.1
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+ - Transformers 4.42.3
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+ - Pytorch 2.1.2+cu118
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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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": "UnfilteredAI/NSFW-3B",
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+ "bias": "none",
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+ "fan_in_fan_out": null,
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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": 16,
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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": 32,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "o_proj",
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+ "down_proj",
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+ "v_proj",
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+ "k_proj",
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+ "up_proj",
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+ "q_proj",
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+ "gate_proj"
30
+ ],
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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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+ {
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+ "_name_or_path": "UnfilteredAI/NSFW-3B",
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+ "architectures": [
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+ "CohereForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "auto_map": {
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+ "AutoConfig": "configuration_HelpingAI.HelpingAIConfig",
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+ "AutoModelForCausalLM": "UnfilteredAI/NSFW-3B--modeling_HelpingAI.HelpingAIForCausalLM"
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+ },
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+ "bos_token_id": 50278,
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+ "classifier_dropout": 0.1,
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+ "eos_token_id": 50279,
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+ "head_dim": 256,
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+ "hidden_act": "silu",
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+ "hidden_activation": null,
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+ "hidden_dropout": 0.0,
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+ "hidden_size": 2560,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 6912,
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 4096,
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+ "model_type": "HelpingAI",
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+ "norm_eps": 1e-05,
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+ "num_attention_heads": 32,
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+ "num_experts_per_tok": 2,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 32,
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+ "num_local_experts": 8,
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+ "output_router_logits": false,
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+ "partial_rotary_factor": 0.25,
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+ "quantization_config": {
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+ "_load_in_4bit": true,
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+ "_load_in_8bit": false,
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+ "bnb_4bit_compute_dtype": "bfloat16",
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+ "bnb_4bit_quant_storage": "bfloat16",
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+ "bnb_4bit_quant_type": "nf4",
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+ "bnb_4bit_use_double_quant": true,
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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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+ "llm_int8_skip_modules": null,
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+ "llm_int8_threshold": 6.0,
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+ "load_in_4bit": true,
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+ "load_in_8bit": false,
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+ "quant_method": "bitsandbytes"
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+ },
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+ "rms_norm_eps": 1e-06,
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+ "rope_pct": 0.25,
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+ "rope_scaling": null,
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+ "rope_theta": 10000,
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+ "router_aux_loss_coef": 0.02,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float16",
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+ "transformers_version": "4.42.3",
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+ "use_cache": false,
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+ "use_qkv_bias": false,
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+ "vocab_size": 50281
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+ }
configuration_HelpingAI.py ADDED
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+ """ HelpingAI model configuration"""
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+
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+ from transformers import PretrainedConfig
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+ from transformers.utils import logging
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+
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+
7
+ logger = logging.get_logger(__name__)
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+
9
+
10
+ class HelpingAIConfig(PretrainedConfig):
11
+ model_type = "HelpingAI"
12
+ keys_to_ignore_at_inference = ["past_key_values"]
13
+
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+ def __init__(
15
+ self,
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+ vocab_size=50281,
17
+ hidden_size=2560,
18
+ num_hidden_layers=32,
19
+ num_attention_heads=32,
20
+ head_dim=256,
21
+ num_local_experts=8,
22
+ num_experts_per_tok=2,
23
+ intermediate_size=6912,
24
+ hidden_act="silu",
25
+ hidden_dropout=0.0,
26
+ attention_dropout=0.0,
27
+ classifier_dropout=0.1,
28
+ max_position_embeddings=4096,
29
+ initializer_range=0.02,
30
+ rms_norm_eps=1e-6,
31
+ layer_norm_eps=1e-5,
32
+ use_cache=False,
33
+ bos_token_id=50278,
34
+ eos_token_id=50279,
35
+ pad_token_id=50279,
36
+ tie_word_embeddings=False,
37
+ rope_pct=0.25,
38
+ rope_theta=10000,
39
+ partial_rotary_factor=0.25,
40
+ use_qkv_bias=False,
41
+ output_router_logits=False,
42
+ router_aux_loss_coef=0.02,
43
+ **kwargs,
44
+ ):
45
+ super().__init__(bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)
46
+ self.vocab_size = vocab_size
47
+ self.max_position_embeddings = max_position_embeddings
48
+ self.hidden_size = hidden_size
49
+ self.num_hidden_layers = num_hidden_layers
50
+ self.num_attention_heads = num_attention_heads
51
+ self.head_dim = head_dim
52
+ self.num_local_experts = num_local_experts
53
+ self.num_experts_per_tok = num_experts_per_tok
54
+ self.intermediate_size = intermediate_size
55
+ self.hidden_act = hidden_act
56
+ self.hidden_dropout = hidden_dropout
57
+ self.attention_dropout = attention_dropout
58
+ self.classifier_dropout = classifier_dropout
59
+ self.initializer_range = initializer_range
60
+ self.rms_norm_eps = rms_norm_eps
61
+ self.layer_norm_eps = layer_norm_eps
62
+ self.use_cache = use_cache
63
+ self.tie_word_embeddings = tie_word_embeddings
64
+ self.rope_pct = rope_pct
65
+ self.rope_theta = rope_theta
66
+ self.partial_rotary_factor = partial_rotary_factor
67
+ self.use_qkv_bias = use_qkv_bias
68
+ self.output_router_logits = output_router_logits
69
+ self.router_aux_loss_coef = router_aux_loss_coef
70
+
71
+ if self.hidden_size % self.num_attention_heads != 0:
72
+ raise ValueError(
73
+ "The hidden size is not divisble by the number of attention heads! Make sure to update them!"
74
+ )
75
+
76
+ # Copied from transformers.models.llama.configuration_llama.LlamaConfig._rope_scaling_validation
77
+ def _rope_scaling_validation(self):
78
+ """
79
+ Validate the `rope_scaling` configuration.
80
+ """
81
+ if self.rope_scaling is None:
82
+ return
83
+
84
+ if not isinstance(self.rope_scaling, dict) or len(self.rope_scaling) != 2:
85
+ raise ValueError(
86
+ "`rope_scaling` must be a dictionary with two fields, `type` and `factor`, " f"got {self.rope_scaling}"
87
+ )
88
+ rope_scaling_type = self.rope_scaling.get("type", None)
89
+ rope_scaling_factor = self.rope_scaling.get("factor", None)
90
+ if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
91
+ raise ValueError(
92
+ f"`rope_scaling`'s type field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"
93
+ )
94
+ if rope_scaling_factor is None or not isinstance(rope_scaling_factor, float) or rope_scaling_factor <= 1.0:
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+ raise ValueError(f"`rope_scaling`'s factor field must be a float > 1, got {rope_scaling_factor}")
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+ }
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+ },
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+ "content": " ",
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+ "lstrip": false,
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+ "normalized": true,
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+ "single_word": false,
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+ },
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+ "single_word": false,
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+ },
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+ "50277": {
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+ "content": "<|pad|>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "single_word": false,
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+ "special": false
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+ },
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+ "50278": {
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+ "content": "<|im_start|>",
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+ "lstrip": false,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "50279": {
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+ "content": "<|im_end|>",
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+ "lstrip": false,
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+ "normalized": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "50280": {
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+ }
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+ },
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+ "additional_special_tokens": [
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+ "<|im_start|>",
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+ "<|im_end|>"
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+ ],
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+ "bos_token": "<|im_start|>",
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+ "chat_template": "{% for message in messages %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
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+ "clean_up_tokenization_spaces": true,
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+ "eos_token": "<|im_end|>",
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+ "model_max_length": 1000000000000000019884624838656,
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+ "pad_token": "[PAD]",
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+ "tokenizer_class": "GPTNeoXTokenizer",
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+ "unk_token": "<|endoftext|>"
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+ }