Token-wise Influential Training Data Retrieval for Large Language Models
Paper • 2405.11724 • Published • 1
An example model for paper "Token-wise Influential Training Data Retrieval for Large Language Models" (Accepted at ACL 2024)
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: float16
Framework versions
- PEFT 0.5.0.dev0
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