Update README.md

README.md

@@ -10,6 +10,7 @@ tags:
 - conversational
 datasets:
 - ajibawa-2023/OpenHermes-2.5-Code-290k
+- teknium/OpenHermes-2.5
 model-index:
 - name: OpenHermes-2.5-Code-290k-13B
   results:
@@ -28,7 +29,8 @@ model-index:
       value: 57.34
       name: normalized accuracy
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -44,7 +46,8 @@ model-index:
       value: 80.48
       name: normalized accuracy
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -61,7 +64,8 @@ model-index:
       value: 56.53
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -77,7 +81,8 @@ model-index:
     - type: mc2
       value: 52.5
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -94,7 +99,8 @@ model-index:
       value: 74.82
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -111,13 +117,15 @@ model-index:
       value: 58.3
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ajibawa-2023/OpenHermes-2.5-Code-290k-13B
       name: Open LLM Leaderboard
 ---
 
 **OpenHermes-2.5-Code-290k-13B**
 
 OpenHermes-2.5-Code-290k-13B is a state of the art Llama-2 Fine-tune, which is trained on additional code dataset.
+This Model is much better than teknium's [model](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B). You can check the **Eval results** below.
 This model is trained on my existing dataset [OpenHermes-2.5-Code-290k](https://huggingface.co/datasets/ajibawa-2023/OpenHermes-2.5-Code-290k). 
 This dataset is amalgamation of two datasets. I have used [OpenHermes-2.5](https://huggingface.co/datasets/teknium/OpenHermes-2.5) a super quality dataset made avaliable by teknium. Other datset is my own [Code-290k-ShareGPT](https://huggingface.co/datasets/ajibawa-2023/Code-290k-ShareGPT). 
 Dataset is in Vicuna/ShareGPT format. There are around **1.29 million** set of conversations. I have cleaned the dataset provided by Teknium and removed metadata such as "source" & "category" etc. This dataset has primarily synthetically generated instruction and chat samples. 
@@ -179,5 +187,4 @@ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-le
 |MMLU (5-Shot)                    |56.53|
 |TruthfulQA (0-shot)              |52.50|
 |Winogrande (5-shot)              |74.82|
-|GSM8k (5-shot)                   |58.30|
-
+|GSM8k (5-shot)                   |58.30|