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Quantization made by Richard Erkhov.
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Mixtral_7Bx2_MoE - GGUF
- Model creator: https://huggingface.co/cloudyu/
- Original model: https://huggingface.co/cloudyu/Mixtral_7Bx2_MoE/
| Name | Quant method | Size |
| ---- | ---- | ---- |
| [Mixtral_7Bx2_MoE.Q2_K.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q2_K.gguf) | Q2_K | 4.43GB |
| [Mixtral_7Bx2_MoE.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.IQ3_XS.gguf) | IQ3_XS | 4.95GB |
| [Mixtral_7Bx2_MoE.IQ3_S.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.IQ3_S.gguf) | IQ3_S | 5.22GB |
| [Mixtral_7Bx2_MoE.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q3_K_S.gguf) | Q3_K_S | 5.2GB |
| [Mixtral_7Bx2_MoE.IQ3_M.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.IQ3_M.gguf) | IQ3_M | 5.35GB |
| [Mixtral_7Bx2_MoE.Q3_K.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q3_K.gguf) | Q3_K | 5.78GB |
| [Mixtral_7Bx2_MoE.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q3_K_M.gguf) | Q3_K_M | 5.78GB |
| [Mixtral_7Bx2_MoE.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q3_K_L.gguf) | Q3_K_L | 6.27GB |
| [Mixtral_7Bx2_MoE.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.IQ4_XS.gguf) | IQ4_XS | 6.5GB |
| [Mixtral_7Bx2_MoE.Q4_0.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q4_0.gguf) | Q4_0 | 6.78GB |
| [Mixtral_7Bx2_MoE.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.IQ4_NL.gguf) | IQ4_NL | 6.85GB |
| [Mixtral_7Bx2_MoE.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q4_K_S.gguf) | Q4_K_S | 6.84GB |
| [Mixtral_7Bx2_MoE.Q4_K.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q4_K.gguf) | Q4_K | 7.25GB |
| [Mixtral_7Bx2_MoE.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q4_K_M.gguf) | Q4_K_M | 7.25GB |
| [Mixtral_7Bx2_MoE.Q4_1.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q4_1.gguf) | Q4_1 | 7.52GB |
| [Mixtral_7Bx2_MoE.Q5_0.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q5_0.gguf) | Q5_0 | 8.26GB |
| [Mixtral_7Bx2_MoE.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q5_K_S.gguf) | Q5_K_S | 8.26GB |
| [Mixtral_7Bx2_MoE.Q5_K.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q5_K.gguf) | Q5_K | 8.51GB |
| [Mixtral_7Bx2_MoE.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q5_K_M.gguf) | Q5_K_M | 8.51GB |
| [Mixtral_7Bx2_MoE.Q5_1.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q5_1.gguf) | Q5_1 | 9.01GB |
| [Mixtral_7Bx2_MoE.Q6_K.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q6_K.gguf) | Q6_K | 9.84GB |
| [Mixtral_7Bx2_MoE.Q8_0.gguf](https://huggingface.co/RichardErkhov/cloudyu_-_Mixtral_7Bx2_MoE-gguf/blob/main/Mixtral_7Bx2_MoE.Q8_0.gguf) | Q8_0 | 12.75GB |
Original model description:
---
license: cc-by-nc-4.0
model-index:
- name: Mixtral_7Bx2_MoE
results:
- task:
type: text-generation
name: Text Generation
dataset:
name: AI2 Reasoning Challenge (25-Shot)
type: ai2_arc
config: ARC-Challenge
split: test
args:
num_few_shot: 25
metrics:
- type: acc_norm
value: 71.25
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_7Bx2_MoE
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: HellaSwag (10-Shot)
type: hellaswag
split: validation
args:
num_few_shot: 10
metrics:
- type: acc_norm
value: 87.45
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_7Bx2_MoE
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: MMLU (5-Shot)
type: cais/mmlu
config: all
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 64.98
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_7Bx2_MoE
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: TruthfulQA (0-shot)
type: truthful_qa
config: multiple_choice
split: validation
args:
num_few_shot: 0
metrics:
- type: mc2
value: 67.23
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_7Bx2_MoE
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: Winogrande (5-shot)
type: winogrande
config: winogrande_xl
split: validation
args:
num_few_shot: 5
metrics:
- type: acc
value: 81.22
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_7Bx2_MoE
name: Open LLM Leaderboard
- task:
type: text-generation
name: Text Generation
dataset:
name: GSM8k (5-shot)
type: gsm8k
config: main
split: test
args:
num_few_shot: 5
metrics:
- type: acc
value: 68.46
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_7Bx2_MoE
name: Open LLM Leaderboard
---
# Mixtral MOE 2x7B
MoE of the following models :
* [NurtureAI/neural-chat-7b-v3-16k](https://huggingface.co/NurtureAI/neural-chat-7b-v3-16k)
* [mncai/mistral-7b-dpo-v6](https://huggingface.co/mncai/mistral-7b-dpo-v6)
* metrics:
Average 73.43
ARC 71.25
HellaSwag 87.45
gpu code example
```
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
import math
## v2 models
model_path = "cloudyu/Mixtral_7Bx2_MoE"
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_7Bx2_MoE"
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](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_cloudyu__Mixtral_7Bx2_MoE)
| Metric |Value|
|---------------------------------|----:|
|Avg. |73.43|
|AI2 Reasoning Challenge (25-Shot)|71.25|
|HellaSwag (10-Shot) |87.45|
|MMLU (5-Shot) |64.98|
|TruthfulQA (0-shot) |67.23|
|Winogrande (5-shot) |81.22|
|GSM8k (5-shot) |68.46|