Training procedure
The following bitsandbytes quantization config was used during training:
- quant_method: bitsandbytes
- load_in_8bit: True
- load_in_4bit: False
- 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: fp4
- bnb_4bit_use_double_quant: False
- bnb_4bit_compute_dtype: float32
Framework versions
- PEFT 0.5.0
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from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("/home/yanglet/.cache/huggingface/hub/models--daryl149--Llama-2-13b-chat-hf/snapshots/23c1836b352727e26f31239b79e83c7721684420") model = PeftModel.from_pretrained(base_model, "oliverwang15/FinGPT_v21_Llama2_13B_Sentiment_LLM_Instruction_LoRA_FT_8bit")