Create README.md
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README.md
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---
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library_name: transformers
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license: llama3
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base_model: meta-llama/Llama-3.3-70B-Instruct
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tags:
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- generated_from_trainer
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model-index:
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- name: L3.3-70B-Euryale-v2.3
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results: []
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---
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)
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# L3.3-70B-Euryale-v2.3
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A direct replacement / successor to Euryale v2.2, not Hanami-x1, though it is slightly better in my opinion.
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Recommended Model Settings | *Look, I just use these, they work fine enough. I don't even know how DRY or other meme samplers work. Your system prompt matters more anyway.*
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```
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Prompt Format: Llama-3-Instruct
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Temperature: 1.1
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min_p: 0.1
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```
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Future-ish plans:
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<br>\- Complete this model series.
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<br>\- Further refine the Datasets used for quality, more secondary chats, more creative-related domains. (Inspired by Drummer)
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<br>\- Work on my other incomplete projects. About half a dozen on the backburner for a while now.
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Special thanks to my wallet for funding this, my juniors who share a single braincell between them, and my current national service.
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<br>Have a good day, don't shit yourselves friends. I had a nasty call today.
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Also sorry for the inactivity. Life was in the way. It still is, just less so, for now. Burnout is a thing, huh?
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https://sao10k.carrd.co/ for contact.
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---
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[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
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<details><summary>See axolotl config</summary>
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axolotl version: `0.5.2`
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```yaml
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base_model: meta-llama/Llama-3.3-70B-Instruct
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model_type: AutoModelForCausalLM
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tokenizer_type: AutoTokenizer
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load_in_8bit: false
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load_in_4bit: false
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strict: false
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sequence_len: 16384
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bf16: auto
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fp16:
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tf32: false
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flash_attention: true
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adapter: lora
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lora_model_dir:
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lora_r: 128
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lora_alpha: 16
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lora_dropout: 0.1
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lora_target_linear: true
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lora_fan_in_fan_out:
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peft_use_rslora: true
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# Data
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dataset_prepared_path: last_run_prepared
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datasets:
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- path: datasets/amoral-full-sys-prompt.json # Unalignment Data - Cleaned Up from Original, Split to its own file
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type: customllama3
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- path: datasets/mimi-superfix-RP-filtered-fixed.json # RP / Creative-Instruct Data
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type: customllama3
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- path: datasets/hespera-smartshuffle.json # Hesperus-v2-Instruct Data
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type: customllama3
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warmup_steps: 15
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plugins:
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- axolotl.integrations.liger.LigerPlugin
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liger_rope: true
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liger_rms_norm: true
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liger_layer_norm: true
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liger_glu_activation: true
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liger_fused_linear_cross_entropy: true
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# Iterations
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num_epochs: 1
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# Batching
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gradient_accumulation_steps: 4
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micro_batch_size: 1
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gradient_checkpointing: "unsloth"
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# Optimizer
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optimizer: paged_ademamix_8bit
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lr_scheduler: cosine
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learning_rate: 0.000004
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weight_decay: 0.1
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max_grad_norm: 25.0
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# Iterations
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num_epochs: 1
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# Misc
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deepspeed: ./deepspeed_configs/zero3_bf16.json
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```
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</details><br>
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