初始化项目，由ModelHub XC社区提供模型
Model: Badgids/Gonzo-Chat-7B 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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language:
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- en
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license: apache-2.0
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library_name: transformers
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tags:
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- mergekit
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- merge
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base_model:
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- Nondzu/Mistral-7B-Instruct-v0.2-code-ft
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- NousResearch/Nous-Hermes-2-Mistral-7B-DPO
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- cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
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- eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
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model-index:
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- name: Gonzo-Chat-7B
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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: 65.02
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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=Badgids/Gonzo-Chat-7B
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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: 85.4
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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=Badgids/Gonzo-Chat-7B
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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: 63.75
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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=Badgids/Gonzo-Chat-7B
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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: 60.23
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source:
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url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Badgids/Gonzo-Chat-7B
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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: 77.74
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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=Badgids/Gonzo-Chat-7B
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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: 47.61
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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=Badgids/Gonzo-Chat-7B
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name: Open LLM Leaderboard
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---
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# Gonzo-Chat-7B
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Gonzo-Chat-7B is a merged LLM based on Mistral v0.01 with a 8192 Context length that likes to chat, roleplay, work with agents, do some lite programming, and then beat the brakes off you in the back alley...
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The ***BEST*** Open Source 7B **Street Fighting** LLM of 2024!!!
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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_Badgids__Gonzo-Chat-7B)
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| Metric | Value |
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| --------------------------------- | ----: |
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| Avg. | 66.63 |
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| AI2 Reasoning Challenge (25-Shot) | 65.02 |
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| HellaSwag (10-Shot) | 85.40 |
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| MMLU (5-Shot) | 63.75 |
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| TruthfulQA (0-shot) | 60.23 |
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| Winogrande (5-shot) | 77.74 |
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| GSM8k (5-shot) | 47.61 |
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## LLM-Colosseum Results
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All contestents fought using the same LLM-Colosseum default settings. Each contestant fought 25 rounds with every other contestant.
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https://github.com/OpenGenerativeAI/llm-colosseum
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### Gonzo-Chat-7B .vs Mistral v0.2, Dolphon-Mistral v0.2, Deepseek-Coder-6.7b-instruct
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO](https://huggingface.co/eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO) as a base.
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### Models Merged
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The following models were included in the merge:
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* [Nondzu/Mistral-7B-Instruct-v0.2-code-ft](https://huggingface.co/Nondzu/Mistral-7B-Instruct-v0.2-code-ft)
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* [NousResearch/Nous-Hermes-2-Mistral-7B-DPO](https://huggingface.co/NousResearch/Nous-Hermes-2-Mistral-7B-DPO)
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* [cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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models:
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- model: eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
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# No parameters necessary for base model
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- model: cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
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parameters:
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density: 0.53
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weight: 0.4
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- model: NousResearch/Nous-Hermes-2-Mistral-7B-DPO
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parameters:
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density: 0.53
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weight: 0.3
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- model: Nondzu/Mistral-7B-Instruct-v0.2-code-ft
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parameters:
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density: 0.53
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weight: 0.3
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merge_method: dare_ties
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base_model: eren23/ogno-monarch-jaskier-merge-7b-OH-PREF-DPO
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parameters:
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int8_mask: true
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dtype: bfloat16
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```
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