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Model: cloudyu/Mixtral_11Bx2_MoE_19B Source: Original Platform
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README.md
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README.md
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---
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license: cc-by-nc-4.0
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model-index:
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- name: Mixtral_11Bx2_MoE_19B
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results:
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: AI2 Reasoning Challenge (25-Shot)
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type: ai2_arc
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config: ARC-Challenge
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split: test
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args:
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num_few_shot: 25
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metrics:
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- type: acc_norm
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value: 71.16
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: HellaSwag (10-Shot)
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type: hellaswag
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split: validation
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args:
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num_few_shot: 10
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metrics:
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- type: acc_norm
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value: 88.47
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name: normalized accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: MMLU (5-Shot)
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type: cais/mmlu
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config: all
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 66.31
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: TruthfulQA (0-shot)
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type: truthful_qa
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config: multiple_choice
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split: validation
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args:
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num_few_shot: 0
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metrics:
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- type: mc2
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value: 72.0
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: Winogrande (5-shot)
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type: winogrande
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config: winogrande_xl
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split: validation
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 83.27
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B
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name: Open LLM Leaderboard
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- task:
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type: text-generation
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name: Text Generation
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dataset:
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name: GSM8k (5-shot)
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type: gsm8k
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config: main
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split: test
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args:
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num_few_shot: 5
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metrics:
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- type: acc
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value: 65.28
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name: accuracy
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/Mixtral_11Bx2_MoE_19B
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name: Open LLM Leaderboard
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---
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# Mixtral MOE 2x10.7B
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[One of Best MoE Model reviewd by reddit community](https://www.reddit.com/r/LocalLLaMA/comments/1916896/llm_comparisontest_confirm_leaderboard_big_news/)
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MoE of the following models :
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* [kyujinpy/Sakura-SOLAR-Instruct](https://huggingface.co/kyujinpy/Sakura-SOLAR-Instruct)
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* [jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1)
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* Local Test
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* hf (pretrained=cloudyu/Mixtral_11Bx2_MoE_19B), gen_kwargs: (None), limit: None, num_fewshot: 10, batch_size: auto (32)
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| Tasks |Version|Filter|n-shot| Metric |Value | |Stderr|
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|---------|-------|------|-----:|--------|-----:|---|-----:|
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|hellaswag|Yaml |none | 10|acc |0.7142|± |0.0045|
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| | |none | 10|acc_norm|0.8819|± |0.0032|
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gpu code example
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```
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import math
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## v2 models
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model_path = "cloudyu/Mixtral_11Bx2_MoE_19B"
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tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False)
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model = AutoModelForCausalLM.from_pretrained(
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model_path, torch_dtype=torch.float32, device_map='auto',local_files_only=False, load_in_4bit=True
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)
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print(model)
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prompt = input("please input prompt:")
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while len(prompt) > 0:
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to("cuda")
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generation_output = model.generate(
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input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2
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)
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print(tokenizer.decode(generation_output[0]))
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prompt = input("please input prompt:")
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```
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CPU example
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```
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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import math
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## v2 models
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model_path = "cloudyu/Mixtral_11Bx2_MoE_19B"
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tokenizer = AutoTokenizer.from_pretrained(model_path, use_default_system_prompt=False)
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model = AutoModelForCausalLM.from_pretrained(
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model_path, torch_dtype=torch.float32, device_map='cpu',local_files_only=False
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)
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print(model)
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prompt = input("please input prompt:")
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while len(prompt) > 0:
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids
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generation_output = model.generate(
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input_ids=input_ids, max_new_tokens=500,repetition_penalty=1.2
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)
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print(tokenizer.decode(generation_output[0]))
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prompt = input("please input prompt:")
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```
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# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_cloudyu__Mixtral_11Bx2_MoE_19B)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |74.41|
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|AI2 Reasoning Challenge (25-Shot)|71.16|
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|HellaSwag (10-Shot) |88.47|
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|MMLU (5-Shot) |66.31|
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|TruthfulQA (0-shot) |72.00|
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|Winogrande (5-shot) |83.27|
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|GSM8k (5-shot) |65.28|
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