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RedHatAI/mpt-7b-gsm8k-pruned50-quant-ds

By RedHatAI · ↓ 5 · ♥ 0 · Updated 2023-10-12

What's in this repo

This page lists the files in RedHatAI/mpt-7b-gsm8k-pruned50-quant-ds, including model-orig.onnx, model.onnx.

  • 2 ONNX models (.onnx files)
  • 9 files, including 4 .json, 2 .onnx, 1 .md, 1 .data
  • Last updated 2023-10-12

ONNX files

File Size Download
model-orig.onnx — Download
model.onnx — Download

How to use

These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.

README

mpt-7b-gsm8k-pruned50-quant

Paper: Sparse Finetuning for Inference Acceleration of Large Language Models
Code: https://github.com/neuralmagic/deepsparse/tree/main/research/mpt

This model was produced from a MPT-7B base model finetuned on the GSM8k dataset with pruning applied using SparseGPT and retrain for 2 epochs with L2 distillation. Then it was exported for optimized inference with DeepSparse.

GSM8k zero-shot accuracy with lm-evaluation-harness : 30.71% (FP32 baseline is 28.2%)

Usage

from deepsparse import TextGeneration
model_path = "hf:neuralmagic/mpt-7b-gsm8k-pruned50-quant" # or use a sparsezoo stub (zoo:mpt-7b-gsm8k_mpt_pretrain-pruned50_quantized)
model = TextGeneration(model=model_path)
model("There are twice as many boys as girls at Dr. Wertz's school. If there are 60 girls and 5 students to every teacher, how many teachers are there?", max_new_tokens=50)

All MPT model weights are available on SparseZoo and CPU speedup for generative inference can be reproduced by following the instructions at DeepSparse

Model Links Compression
neuralmagic/mpt-7b-gsm8k-quant Quantization (W8A8)
neuralmagic/mpt-7b-gsm8k-pruned40-quant Quantization (W8A8) & 40% Pruning
neuralmagic/mpt-7b-gsm8k-pruned50-quant Quantization (W8A8) & 50% Pruning
neuralmagic/mpt-7b-gsm8k-pruned60-quant Quantization (W8A8) & 60% Pruning
neuralmagic/mpt-7b-gsm8k-pruned70-quant Quantization (W8A8) & 70% Pruning
neuralmagic/mpt-7b-gsm8k-pruned70-quant Quantization (W8A8) & 75% Pruning
neuralmagic/mpt-7b-gsm8k-pruned80-quant Quantization (W8A8) & 80% Pruning

For general questions on these models and sparsification methods, reach out to the engineering team on our community Slack.

Model info

text-generation transformers
transformers onnx mpt text-generation deepsparse custom_code dataset:gsm8k arxiv:2310.06927 arxiv:2301.00774 region:us
↓ 5 ♥ 0

Created: 2023-09-29

Updated: 2023-10-12

View on Hugging Face

Files (9)

.gitattributes
README.md
config.json
model-orig.onnx ONNX
model.data
model.onnx ONNX
special_tokens_map.json
tokenizer.json
tokenizer_config.json

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