Thireus's picture
Update README.md
7951b59
|
raw
history blame
3.04 kB
metadata
inference: false
license: llama2
model_creator: WizardLM
model_link: https://huggingface.co./WizardLM/WizardLM-70B-V1.0
model_name: WizardLM 70B V1.0
model_type: llama
quantized_by: Thireus

WizardLM 70B V1.0 - EXL2

Branch BITS (-b) HEAD BITS (-hb) MEASUREMENT LENGTH (-ml) LENGTH (-l) CAL DATASET (-c) Size ExLlama Max Context Length
main 4.0 6 2048 2048 0000.parquet (wikitext-2-raw-v1) 33GB V2 4096

Description

This repository contains EXL2 model files for WizardLM's WizardLM 70B V1.0.

EXL2 is a new format used by ExLlamaV2 - https://github.com/turboderp/exllamav2. EXL2 is based on the same optimization method as GPTQ. The format allows for mixing quantization levels within a model to achieve any average bitrate between 2 and 8 bits per weight.

Prompt template (official): Vicuna

A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions. USER: {prompt} ASSISTANT:

Prompt template (Thireus' own suggestion):

A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
USER:
{prompt}
ASSISTANT:

Quantization process

Original Model --> Float16 Model --> Safetensor Model --> EXL2 Model

Example:

WizardLM 70B V1.0 --> WizardLM 70B V1.0-HF --> Safetensor --> EXL2

Use any one of the following scripts to convert your float16 pytorch_model bin files to safetensors:

Example to convert WizardLM-70B-V1.0-HF_float16_safetensored to EXL2 4.0 bpw with 6-bit head:

mkdir -p ~/EXL2/WizardLM-70B-V1.0-HF_4bit # Create the output directory
python convert.py -i ~/safetensor/WizardLM-70B-V1.0-HF_float16_safetensored -o ~/EXL2/WizardLM-70B-V1.0-HF_4bit -c ~/EXL2/0000.parquet -b 4.0 -hb 6