初始化项目，由ModelHub XC社区提供模型
Model: cloudyu/Mixtral_7Bx4_MOE_24B Source: Original Platform
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ModelHub XC
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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_7bx4_moe
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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: 65.27
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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_7bx4_moe
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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: 85.28
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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_7bx4_moe
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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: 62.84
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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_7bx4_moe
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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: 59.85
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cloudyu/mixtral_7bx4_moe
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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: 77.66
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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_7bx4_moe
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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: 62.09
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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_7bx4_moe
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name: Open LLM Leaderboard
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---
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I don't know why so many downloads about this model.
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Please share your cases, thanks.
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Now this model is improved by DPO to [cloudyu/Pluto_24B_DPO_200](https://huggingface.co/cloudyu/Pluto_24B_DPO_200)
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* Metrics improved by DPO
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# Mixtral MOE 4x7B
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MOE the following models by mergekit:
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* [Q-bert/MetaMath-Cybertron-Starling](https://huggingface.co/Q-bert/MetaMath-Cybertron-Starling)
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* [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
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* [teknium/Mistral-Trismegistus-7B](https://huggingface.co/teknium/Mistral-Trismegistus-7B)
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* [meta-math/MetaMath-Mistral-7B](https://huggingface.co/meta-math/MetaMath-Mistral-7B)
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* [openchat/openchat-3.5-1210](https://huggingface.co/openchat/openchat-3.5-1210)
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Metrics
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* Average : 68.85
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* ARC:65.36
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* HellaSwag:85.23
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* more details: https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/cloudyu/Mixtral_7Bx4_MOE_24B/results_2023-12-23T18-05-51.243288.json
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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_7Bx4_MOE_24B"
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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_7Bx4_MOE_24B"
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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_7bx4_moe)
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| Metric |Value|
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|---------------------------------|----:|
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|Avg. |68.83|
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|AI2 Reasoning Challenge (25-Shot)|65.27|
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|HellaSwag (10-Shot) |85.28|
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|MMLU (5-Shot) |62.84|
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|TruthfulQA (0-shot) |59.85|
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|Winogrande (5-shot) |77.66|
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|GSM8k (5-shot) |62.09|
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