Paul Rock
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Readme tuned, generation_config.json added
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- generation_config.json +15 -0
README.md
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- adapter
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# ruGPT-3.5 13B LoRA
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The following `bitsandbytes` quantization config was used during training:
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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- PyTorch 2.1.0
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- PEFT 0.5.0
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- adapter
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# ruGPT-3.5 13B LoRA: Adapter-Only Version
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Welcome to the adapter-only version of ruGPT-3.5 13B LoRA. This model is built upon the foundation of [ruGPT-3.5-13B](https://huggingface.co/ai-forever/ruGPT-3.5-13B).
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π Important: This model was trained using settings identical to [GigaSaiga](https://huggingface.co/IlyaGusev/gigasaiga_lora), but incorporates two additional datasets.
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π Training code is [here](https://github.com/EvilFreelancer/ruGPT-3.5-13B-lora).
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> Note: If you prefer, you can opt to use the ruGPT-3.5 13B fp16 base model.
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## π Training Datasets
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The datasets utilized for training this model are consistent with those used for [Saiga-2](https://github.com/IlyaGusev/rulm).
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Here's the comprehensive list:
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- [ru_turbo_alpaca](https://huggingface.co/datasets/IlyaGusev/ru_turbo_alpaca)
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- [ru_turbo_alpaca_evol_instruct](https://huggingface.co/datasets/IlyaGusev/ru_turbo_alpaca_evol_instruct)
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- [ru_turbo_saiga](https://huggingface.co/datasets/IlyaGusev/ru_turbo_saiga)
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- [ru_sharegpt_cleaned](https://huggingface.co/datasets/IlyaGusev/ru_sharegpt_cleaned)
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- [oasst1_ru_main_branch](https://huggingface.co/datasets/IlyaGusev/oasst1_ru_main_branch)
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- [gpt_roleplay_realm](https://huggingface.co/datasets/IlyaGusev/gpt_roleplay_realm)
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- [ru_instruct_gpt4](https://huggingface.co/datasets/lksy/ru_instruct_gpt4)
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## π Training Procedure
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The following `bitsandbytes` quantization config was used during training:
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- bnb_4bit_use_double_quant: False
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- bnb_4bit_compute_dtype: float32
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## βοΈ Framework Versions
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Ensure you have the following framework versions for compatibility:
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- PyTorch 2.1.0
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- PEFT 0.5.0
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 2,
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"eos_token_id": 3,
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"pad_token_id": 0,
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"transformers_version": "4.34.0",
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"temperature": 0.2,
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"top_p": 0.9,
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"top_k": 30,
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"do_sample": true,
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"max_new_tokens": 1536,
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"num_beams": 1,
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"repetition_penalty": 1.15,
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"no_repeat_ngram_size": 15
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}
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