初始化项目，由ModelHub XC社区提供模型

Model: ajibawa-2023/Code-Mistral-7B
Source: Original Platform

README.md

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+---
+language:
+- en
+license: apache-2.0
+tags:
+- code
+- mathematics
+datasets:
+- ajibawa-2023/Code-290k-ShareGPT
+- m-a-p/Code-Feedback
+- microsoft/orca-math-word-problems-200k
+- teknium/openhermes
+model-index:
+- name: Code-Mistral-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: 64.59
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-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: 85.29
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-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: 65.0
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-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: 54.64
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-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: 82.24
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-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: 68.08
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-Mistral-7B
+      name: Open LLM Leaderboard
+---
+
+**Code-Mistral-7B**
+
+
+This Model is trained on refined version of my dataset [Code-290k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Code-290k-ShareGPT).
+
+Besides this it is trained on following datasets:
+
+[Code-Feedback](https://huggingface.co/datasets/m-a-p/Code-Feedback)
+
+[orca-math-word-problems-200k](https://huggingface.co/datasets/microsoft/orca-math-word-problems-200k)
+
+[Openhermes](https://huggingface.co/datasets/teknium/openhermes)
+
+The idea was to check how this Model will perform with both Code & Maths datasets. This model is very good with Coding. 
+Maths is still hit & miss but you can test out this model.
+
+This Model is trained on massive datasets so the results are very good.
+I have used ChatML prompt format.
+
+Kindly note this is qLoRA version, a rare exception.
+
+**GGUF & Exllama**
+
+GGUF: [Link](https://huggingface.co/bartowski/Code-Mistral-7B-GGUF)
+
+Exllama v2: [Link](https://huggingface.co/bartowski/Code-Mistral-7B-exl2)
+
+Special Thanks to [Bartowski](https://huggingface.co/bartowski) for quantizing this model.
+
+
+**Training:**
+
+Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took almost 33 Hours. Axolotl codebase was used for training purpose.
+Entire data is trained on Mistral.
+
+**Example Prompt:**
+This model uses **ChatML** prompt format.
+
+```
+<|im_start|>system
+You are a helpful AI assistant.<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+
+```
+You can modify above Prompt as per your requirement. 
+
+
+I want to say special Thanks to the Open Source community for helping & guiding me to better understand the AI/Model development.
+
+Thank you for your love & support.
+
+
+**Example Output**
+
+
+**C++**
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/jcmEZSRX7s7-B_ZybWwwN.jpeg)
+
+**Error Resolving**
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/iy89IxjiZXAY4Id-ieLg7.jpeg)
+
+**Matrices**
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/zFfq9lBA63wQzy0tP3_hd.jpeg)
+
+**Machine Learning**
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/Nv8dCpNxRtJGkOuulKzmn.jpeg)
+
+
+
+# [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_ajibawa-2023__Code-Mistral-7B)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |69.97|
+|AI2 Reasoning Challenge (25-Shot)|64.59|
+|HellaSwag (10-Shot)              |85.29|
+|MMLU (5-Shot)                    |65.00|
+|TruthfulQA (0-shot)              |54.64|
+|Winogrande (5-shot)              |82.24|
+|GSM8k (5-shot)                   |68.08|
+