--- base_model: upstage/SOLAR-10.7B-Instruct-v1.0 license: cc-by-nc-4.0 datasets: - teknium/openhermes - garage-bAInd/Open-Platypus - LDJnr/Capybara --- Fine-tune of Upstage AI's SOLAR-10.7B-Instruct-v1.0 model, using the OpenHermes, Platypus, and Capybara datasets. Fine-tuned on 8x4090s for 1.25 epochs. ### Model Sources [optional] - **Repository:** TBD - **Demo:** TBD ## Bias, Risks, and Limitations This fine-tune has had zero alignment, safety data, or anything else shoved down it's throat. ## Training Details ### Training Data See the sidebar for links to the relevant datasets. ### Training Procedure Trained using QLORA via the Axolotl tool. ## Evaluation TBD ## Training procedure The following `bitsandbytes` quantization config was used during training: - quant_method: bitsandbytes - load_in_8bit: False - load_in_4bit: True - llm_int8_threshold: 6.0 - llm_int8_skip_modules: None - llm_int8_enable_fp32_cpu_offload: False - llm_int8_has_fp16_weight: False - bnb_4bit_quant_type: nf4 - bnb_4bit_use_double_quant: True - bnb_4bit_compute_dtype: bfloat16 ### Framework versions - PEFT 0.6.0