README.md

metadata

license: cc-by-nc-4.0

Mixtral MOE 2x10.7B

MoE of the following models by powerful mergekit :

• kyujinpy/Sakura-SOLAR-Instruct

• jeonsworld/CarbonVillain-en-10.7B-v1

• Local Test

• hf (pretrained=cloudyu/Mixtral_11Bx2_MoE_19B,load_in_8bit=True), gen_kwargs: (None), limit: None, num_fewshot: None, batch_size: 64

  Tasks	Version	Filter	n-shot	Metric	Value		Stderr
  hellaswag	Yaml	none	0	acc	0.6911	±	0.0046
  		none	0	acc_norm	0.8647	±	0.0034

gpu code example

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
import math

## v2 models
model_path = "cloudyu/Mixtral_11Bx2_MoE_19B"

tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False)
model = AutoModelForCausalLM.from_pretrained(
    model_path, torch_dtype=torch.float32, device_map='auto',local_files_only=False, load_in_4bit=True
)
print(model)
prompt = input("please input prompt:")
while len(prompt) > 0:
  input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to("cuda")

  generation_output = model.generate(
    input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2
  )
  print(tokenizer.decode(generation_output[0]))
  prompt = input("please input prompt:")

CPU example

import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
import math

## v2 models
model_path = "cloudyu/Mixtral_11Bx2_MoE_19B"

tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False)
model = AutoModelForCausalLM.from_pretrained(
    model_path, torch_dtype=torch.float32, device_map='cpu',local_files_only=False
)
print(model)
prompt = input("please input prompt:")
while len(prompt) > 0:
  input_ids = tokenizer(prompt, return_tensors="pt").input_ids

  generation_output = model.generate(
    input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2
  )
  print(tokenizer.decode(generation_output[0]))
  prompt = input("please input prompt:")