SQCU/greener-13-2-base-8bitC

OVERVIEW

PEFT model trained on a strided, raw text dataset. Full training parameters are available in training_parameters.json. The most salient model feature is a training context window of 1024 tokens, with each training window overlapped with the last 128 tokens of the previous window. This overlap ratio is unusual and produces objectionable quantitative results in perplexity eval.

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library_name: peft

Training procedure

The following bitsandbytes quantization config was used during training:

• 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

The following bitsandbytes quantization config was used during training:

• 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.dev0

• PEFT 0.5.0.dev0