初始化项目，由ModelHub XC社区提供模型

Model: ajibawa-2023/Code-290k-6.7B-Instruct Source: Original Platform
2026-05-05 20:28:46 +08:00
commit 16d4d572a9
13 changed files with 227497 additions and 0 deletions
--- a/README.md
+++ b/README.md
@@ -0,0 +1,179 @@
+---
+language:
+- en
+license: other
+tags:
+- code
+datasets:
+- ajibawa-2023/Code-290k-ShareGPT
+model-index:
+- name: Code-290k-6.7B-Instruct
+  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: 34.9
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-290k-6.7B-Instruct
+      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: 51.99
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-290k-6.7B-Instruct
+      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: 34.89
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-290k-6.7B-Instruct
+      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: 41.95
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-290k-6.7B-Instruct
+      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: 52.64
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-290k-6.7B-Instruct
+      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: 3.49
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/Code-290k-6.7B-Instruct
+      name: Open LLM Leaderboard
+---
+
+**Code-290k-6.7B-Instruct**
+
+This model is trained on [DeepSeek-Coder-6.7B-Instruct](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-instruct). I have used my existing dataset [Code-290k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Code-290k-ShareGPT) for training purpose.
+It is trained on around 290000 set of codes. Along with Python, Java, JavaScript, GO, C++, Rust, Ruby, Sql, MySql, R, Julia, Haskell, etc. code with detailed explanation is used for training purpose. 
+This model utilises Alpaca format. Besides code generation it will also give you explanation. 
+
+**Training:**
+
+Entire dataset was trained on 4 x A100 80GB. For 3 epoch, training took 85 hours. DeepSeek-Coder codebase and DeepSpeed was used for training purpose.
+
+This is a full fine tuned model.
+
+Links for quantized models are given below.
+
+**Exllama**
+
+Exllama v2:[Link](https://huggingface.co/bartowski/Code-290k-6.7B-Instruct-exl2)
+
+Extremely thankful to [Bartowski](https://huggingface.co/bartowski) for making Quantized version of the model.
+
+
+**Example Prompt**:
+
+```
+This is a conversation with your helpful AI assistant. AI assistant can generate Code in various Programming Languages along with necessary explanation.
+
+### Instruction:
+{instruction}
+
+### Response:
+```
+You can modify above Prompt as per your requirement. I have used Alpaca format.
+
+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.
+
+**Examples** 
+
+1. **Bayes Theorem - Python**
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/J8uqoT_LYhPW2VpnE1K-8.png)
+
+2. **Fermat's little theorem**
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/H0sc9jk7ypv_N5V7LSANl.png)
+
+3. **The Arrhenius equation using R**
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/64aea8ff67511bd3d965697b/BQ8PZhYhoZ9wpVMPXJPnQ.png)
+
+
+# [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-290k-6.7B-Instruct)
+
+|             Metric              |Value|
+|---------------------------------|----:|
+|Avg.                             |36.64|
+|AI2 Reasoning Challenge (25-Shot)|34.90|
+|HellaSwag (10-Shot)              |51.99|
+|MMLU (5-Shot)                    |34.89|
+|TruthfulQA (0-shot)              |41.95|
+|Winogrande (5-shot)              |52.64|
+|GSM8k (5-shot)                   | 3.49|
+