metadata

language:
  - fr
  - it
  - de
  - es
  - en
license: apache-2.0
tags:
  - moe
inference: false

Model Card for Mixtral-Fusion-4x7B-Instruct-v0.1

This model is an experimental model created by merging mistralai/Mixtral-8x7B-Instruct-v0.1 experts.

How we merged experts

Changed to merge using slerp.
Discussion

old merge version
~~We simply take the average of every two experts.weight.~~
~~The same goes for gate.weight.~~

How To Convert

use colab cpu-high-memory.
convert_mixtral_8x7b_to_4x7b.ipynb

OtherModels

mmnga/Mixtral-Extraction-4x7B-Instruct-v0.1

Usage

pip install git+https://github.com/huggingface/transformers --upgrade
pip install torch accelerate bitsandbytes flash_attn

from transformers import AutoTokenizer, AutoModelForCausalLM, MixtralForCausalLM
import torch

model_name_or_path = "mmnga/Mixtral-Fusion-4x7B-Instruct-v0.1"

tokenizer = AutoTokenizer.from_pretrained(model_name_or_path)
model = MixtralForCausalLM.from_pretrained(model_name_or_path, load_in_8bit=True)

text = "[INST] What was John Holt's vision on education? [/INST] "
inputs = tokenizer(text, return_tensors="pt")

outputs = model.generate(**inputs, max_new_tokens=128)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))