Instructions to use willtensora/123e4567-e89b-12d3-a456-426614174000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use willtensora/123e4567-e89b-12d3-a456-426614174000 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("peft-internal-testing/tiny-dummy-qwen2") model = PeftModel.from_pretrained(base_model, "willtensora/123e4567-e89b-12d3-a456-426614174000") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files- README.md +8 -8
- adapter_model.bin +1 -1
README.md
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@@ -38,12 +38,12 @@ deepspeed: null
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early_stopping_patience: null
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eval_max_new_tokens: 128
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eval_table_size: null
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evals_per_epoch:
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flash_attention: false
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fp16: null
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fsdp: null
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fsdp_config: null
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gradient_accumulation_steps:
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gradient_checkpointing: false
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group_by_length: false
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hub_model_id: willtensora/123e4567-e89b-12d3-a456-426614174000
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@@ -62,8 +62,8 @@ lora_model_dir: null
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lora_r: 8
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lora_target_linear: true
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lr_scheduler: cosine
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max_steps:
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micro_batch_size:
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mlflow_experiment_name: argilla/databricks-dolly-15k-curated-en
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model_type: AutoModelForCausalLM
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num_epochs: 1
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@@ -73,21 +73,21 @@ pad_to_sequence_len: true
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resume_from_checkpoint: null
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s2_attention: null
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sample_packing: false
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saves_per_epoch:
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sequence_len:
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strict: false
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tf32: false
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tokenizer_type: AutoTokenizer
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train_on_inputs: false
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trust_remote_code: true
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val_set_size: 0.
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wandb_entity: null
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wandb_mode: online
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wandb_name: 123e4567-e89b-12d3-a456-426614174000
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wandb_project: Gradients-On-Demand
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wandb_run: your_name
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wandb_runid: 123e4567-e89b-12d3-a456-426614174000
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warmup_steps:
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weight_decay: 0.0
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xformers_attention: null
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early_stopping_patience: null
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eval_max_new_tokens: 128
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eval_table_size: null
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evals_per_epoch: 1
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flash_attention: false
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fp16: null
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fsdp: null
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fsdp_config: null
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gradient_accumulation_steps: 1
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gradient_checkpointing: false
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group_by_length: false
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hub_model_id: willtensora/123e4567-e89b-12d3-a456-426614174000
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lora_r: 8
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lora_target_linear: true
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lr_scheduler: cosine
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max_steps: 2
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micro_batch_size: 1
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mlflow_experiment_name: argilla/databricks-dolly-15k-curated-en
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model_type: AutoModelForCausalLM
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num_epochs: 1
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resume_from_checkpoint: null
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s2_attention: null
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sample_packing: false
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saves_per_epoch: 1
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sequence_len: 128
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strict: false
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tf32: false
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tokenizer_type: AutoTokenizer
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train_on_inputs: false
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trust_remote_code: true
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val_set_size: 0.01
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wandb_entity: null
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wandb_mode: online
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wandb_name: 123e4567-e89b-12d3-a456-426614174000
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wandb_project: Gradients-On-Demand
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wandb_run: your_name
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wandb_runid: 123e4567-e89b-12d3-a456-426614174000
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warmup_steps: 2
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weight_decay: 0.0
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xformers_attention: null
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adapter_model.bin
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size 80115210
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version https://git-lfs.github.com/spec/v1
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size 80115210
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