初始化项目，由ModelHub XC社区提供模型

Model: eren23/dpo-binarized-NeutrixOmnibe-7B
Source: Original Platform

README.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- merge
+- dpo
+- conversation
+- text-generation-inference
+- Kukedlc/NeuTrixOmniBe-7B-model-remix
+datasets:
+- argilla/OpenHermes2.5-dpo-binarized-alpha
+pipeline_tag: text-generation
+model-index:
+- name: dpo-binarized-NeutrixOmnibe-7B
+  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: 72.78
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/dpo-binarized-NeutrixOmnibe-7B
+      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: 89.05
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/dpo-binarized-NeutrixOmnibe-7B
+      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: 64.6
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/dpo-binarized-NeutrixOmnibe-7B
+      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: 76.9
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/dpo-binarized-NeutrixOmnibe-7B
+      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: 85.08
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/dpo-binarized-NeutrixOmnibe-7B
+      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: 69.45
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=eren23/dpo-binarized-NeutrixOmnibe-7B
+      name: Open LLM Leaderboard
+---
+
+DPO Finetuned Kukedlc/NeuTrixOmniBe-7B-model-remix using argilla/OpenHermes2.5-dpo-binarized-alpha
+
+argilla dpo binarized pairs is a dataset built on top of: https://huggingface.co/datasets/teknium/OpenHermes-2.5 using https://github.com/argilla-io/distilabel if interested.
+
+Thx for the great data sources.
+
+GGUF: https://huggingface.co/eren23/dpo-binarized-NeutrixOmnibe-7B-GGUF
+# [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_eren23__dpo-binarized-NeutrixOmnibe-7B)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |76.31|
+|AI2 Reasoning Challenge (25-Shot)|72.78|
+|HellaSwag (10-Shot)              |89.05|
+|MMLU (5-Shot)                    |64.60|
+|TruthfulQA (0-shot)              |76.90|
+|Winogrande (5-shot)              |85.08|
+|GSM8k (5-shot)                   |69.45|
+