license, model-index

license

model-index

cc-by-nc-4.0

name results Mixtral_11Bx2_MoE_19B task dataset metrics source type name text-generation Text Generation name type config split args AI2 Reasoning Challenge (25-Shot) ai2_arc ARC-Challenge test num_few_shot 25 type value name acc_norm 71.16 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type split args HellaSwag (10-Shot) hellaswag validation num_few_shot 10 type value name acc_norm 88.47 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args MMLU (5-Shot) cais/mmlu all test num_few_shot 5 type value name acc 66.31 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args TruthfulQA (0-shot) truthful_qa multiple_choice validation num_few_shot 0 type value mc2 72.0 url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args Winogrande (5-shot) winogrande winogrande_xl validation num_few_shot 5 type value name acc 83.27 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args GSM8k (5-shot) gsm8k main test num_few_shot 5 type value name acc 65.28 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B Open LLM Leaderboard

Mixtral MOE 2x10.7B

One of Best MoE Model reviewd by reddit community

MoE of the following models :

• kyujinpy/Sakura-SOLAR-Instruct

• jeonsworld/CarbonVillain-en-10.7B-v1

• Local Test

• hf (pretrained=cloudyu/Mixtral_11Bx2_MoE_19B), gen_kwargs: (None), limit: None, num_fewshot: 10, batch_size: auto (32)

  Tasks	Version	Filter	n-shot	Metric	Value		Stderr
  hellaswag	Yaml	none	10	acc	0.7142	±	0.0045
  		none	10	acc_norm	0.8819	±	0.0032

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:")

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	74.41
AI2 Reasoning Challenge (25-Shot)	71.16
HellaSwag (10-Shot)	88.47
MMLU (5-Shot)	66.31
TruthfulQA (0-shot)	72.00
Winogrande (5-shot)	83.27
GSM8k (5-shot)	65.28