update model card, nice :)

README.md

@@ -64,7 +64,8 @@ model-index:
       value: 64.68
       name: normalized accuracy
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -80,7 +81,8 @@ model-index:
       value: 83.75
       name: normalized accuracy
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -97,7 +99,8 @@ model-index:
       value: 62.31
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -113,7 +116,8 @@ model-index:
     - type: mc2
       value: 55.15
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -130,7 +134,8 @@ model-index:
       value: 76.24
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -147,8 +152,11 @@ model-index:
       value: 57.62
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
+      url: >-
+        https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Weyaxi/Einstein-v4-7B
       name: Open LLM Leaderboard
+language:
+- en
 ---
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6468ce47e134d050a58aa89c/U0zyXVGj-O8a7KP3BvPue.png)
@@ -311,17 +319,6 @@ Quantizationed versions of this model is available.
 
 - https://huggingface.co/bartowski/Einstein-v4-7B-exl2
 
-You can switch up branches in the repo to use the one you want
-
-| Branch | Bits | lm_head bits | VRAM (4k) | VRAM (16k) | VRAM (32k) | Description |
-| ----- | ---- | ------- | ------ | ------ | ------ | ------------ |
-| [8_0](https://huggingface.co/bartowski/Einstein-v4-7B-exl2/tree/8_0) | 8.0 | 8.0 | 8.4 GB | 9.8 GB | 11.8 GB | Maximum quality that ExLlamaV2 can produce, near unquantized performance. |
-| [6_5](https://huggingface.co/bartowski/Einstein-v4-7B-exl2/tree/6_5) | 6.5 | 8.0 | 7.2 GB | 8.6 GB | 10.6 GB | Very similar to 8.0, good tradeoff of size vs performance, **recommended**. |
-| [5_0](https://huggingface.co/bartowski/Einstein-v4-7B-exl2/tree/5_0) | 5.0 | 6.0 | 6.0 GB | 7.4 GB |  9.4 GB | Slightly lower quality vs 6.5, but usable on 8GB cards. |
-| [4_25](https://huggingface.co/bartowski/Einstein-v4-7B-exl2/tree/4_25) | 4.25 | 6.0 | 5.3 GB | 6.7 GB | 8.7 GB | GPTQ equivalent bits per weight, slightly higher quality. |
-| [3_5](https://huggingface.co/bartowski/Einstein-v4-7B-exl2/tree/3_5) | 3.5 | 6.0 | 4.7 GB | 6.1 GB | 8.1 GB | Lower quality, only use if you have to. |
-
-
 # 🎯 [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_Weyaxi__Einstein-v4-7B)
 
@@ -335,6 +332,22 @@ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-le
 |Winogrande (5-shot)              |76.24|
 |GSM8k (5-shot)                   |57.62|
 
+# 📚 Some resources, discussions and reviews aboout this model
+
+#### 🐦 Announcement tweet: 
+
+https://twitter.com/Weyaxi/status/1765851433448944125
+
+#### 🔍 Reddit post in r/LocalLLaMA:
+
+-  https://www.reddit.com/r/LocalLLaMA/comments/1b9gmvl/meet_einsteinv47b_mistralbased_sft_model_using/
+
+#### ▶️ Youtube Videos
+
+- https://www.youtube.com/watch?v=-3YWgHJIORE&t=18s
+
+- https://www.youtube.com/watch?v=Xo2ySU8gja0
+
 # 🤖 Additional information about training
 
 This model is full fine-tuned for 1.5 epoch. 
@@ -360,4 +373,4 @@ Thanks to all open source AI community.
 
 If you would like to support me:
 
-[☕ Buy Me a Coffee](https://www.buymeacoffee.com/weyaxi)
+[☕ Buy Me a Coffee](https://www.buymeacoffee.com/weyaxi)