README.md

superhot-30b-8k-4bit-128g-safetensors

Merged base LLaMA and LoRA with this: https://github.com/tloen/alpaca-lora

Base LLaMA 30B: https://huggingface.co/huggyllama/llama-30b

SuperCOT 30B 8k LoRA: https://huggingface.co/kaiokendev/superhot-30b-8k-no-rlhf-test

BASE_MODEL=huggyllama_llama-30b LORA=kaiokendev_superhot-30b-8k-no-rlhf-test python export_hf_checkpoint.py

Quantized with AutoGPTQ: https://github.com/PanQiWei/AutoGPTQ

python quant_with_alpaca.py --pretrained_model_dir superhot-30b-8k-safetensors --quantized_model_dir superhot-30b-8k-4bit-128g-safetensors --bits 4 --group_size 128 --desc_act --num_samples 256 --save_and_reload

Perplexity:

CUDA_VISIBLE_DEVICES=0 python test_benchmark_inference.py \
         -d /workspace/models/superhot-30b-8k-4bit-128g-safetensors \
         -ppl \
         -ppl_ds datasets/wikitext2.txt \
         -l 8192 \
         -cpe 4 \
         -ppl_cn 40 \
         -ppl_cs 8192 \
         -ppl_ct 8192
 -- Perplexity:
 -- - Dataset: datasets/wikitext2.txt
 -- - Chunks: 40
 -- - Chunk size: 8192 -> 8192
 -- - Chunk overlap: 0
 -- - Min. chunk size: 50
 -- - Key: text
 -- Tokenizer: /workspace/models/superhot-30b-8k-4bit-128g-safetensors/tokenizer.model
 -- Model config: /workspace/models/superhot-30b-8k-4bit-128g-safetensors/config.json
 -- Model: /workspace/models/superhot-30b-8k-4bit-128g-safetensors/4bit-128g.safetensors
 -- Sequence length: 8192
 -- RoPE compression factor: 4.0
 -- Tuning:
 -- --matmul_recons_thd: 8
 -- --fused_mlp_thd: 2
 -- --sdp_thd: 8
 -- Options: ['perplexity']
 ** Time, Load model: 4.31 seconds
 ** Time, Load tokenizer: 0.01 seconds
 -- Groupsize (inferred): 128
 -- Act-order (inferred): yes
 ** VRAM, Model: [cuda:0] 17,043.70 MB
 -- Loading dataset...
 -- Testing 40 chunks....
 ** Perplexity: 4.6612