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---
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base_model: unsloth/Qwen3.5-9B
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library_name: transformers
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model_name: LayLaLLM
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tags:
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- sft
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- unsloth
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---
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This model is a fine-tuned version of [unsloth/Qwen3.5-9B](https://huggingface.co/unsloth/Qwen3.5-9B).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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generator = pipeline("text-generation", model="IoakeimE/LayLaLLM", device="cuda")
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output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
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print(output["generated_text"])
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```
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##
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- Transformers: 5.5.4
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- Pytorch: 2.10.0
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- Datasets: 4.8.4
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- Tokenizers: 0.22.2
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##
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author = {von Werra, Leandro and Belkada, Younes and Tunstall, Lewis and Beeching, Edward and Thrush, Tristan and Lambert, Nathan and Huang, Shengyi and Rasul, Kashif and Gallouédec, Quentin},
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license = {Apache-2.0},
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url = {https://github.com/huggingface/trl},
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year = {2020}
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}
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```
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library_name: peft
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license: apache-2.0
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base_model: unsloth/Qwen3.5-9B
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tags:
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- base_model:adapter:unsloth/Qwen3.5-9B
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- lora
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- sft
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- transformers
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- trl
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- unsloth
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pipeline_tag: text-generation
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model-index:
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- name: LayLaLLM
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/ioakeime-aristotle-university-of-thessaloniki/LayLaLLM/runs/jloynhfg)
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# LayLaLLM
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This model is a fine-tuned version of [unsloth/Qwen3.5-9B](https://huggingface.co/unsloth/Qwen3.5-9B) on an unknown dataset.
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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: 1e-05
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- train_batch_size: 1
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- eval_batch_size: 4
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- seed: 3407
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 16
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- optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_steps: 0.1
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- num_epochs: 1
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### Framework versions
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- PEFT 0.19.1
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- Transformers 5.5.4
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- Pytorch 2.10.0+cu128
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- Datasets 4.8.4
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- Tokenizers 0.22.2
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