Update README.md

README.md

@@ -7,17 +7,32 @@ tags:
 - llama
 - trl
 - dpo
-license: apache-2.0
+license: llama3.2
 language:
 - en
+pipeline_tag: text-generation
 ---
+😁:```Hi Fijik!```
+
+🤖:```Hello! What's up? How may I help?```
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6710ba6af1279fe0dfe33afe/Dub2iaHaWhxfMC_ZGBYtc.png)
+# What is it
+Fijik is a **6 billion** parameter, dense 56 layer transformer LLM based on llama 3.2, specifically, it was merged using Mergekit to be twice as large as llama 3.2 3B.
+
+After merging, we used a custom dataset mix meant for this model, to improve its performance even more.
+- **Step 1 for fine-tuning via unsloth:** SFT on an estimated 20 million tokens. (more or less)
+- **Step 2 for the fine-tuning via unsloth:** DPO for 2 epochs for even better instruction following.
+After these two steps, we got a powerful model which has less parameters than llama 3.1 8B yet performs just as good if not better, Note that unlike our other models, it is not a thinking model. our theory behind this model is that a smaller yet deeper model can outperform for it's size.
+
+Meta states that LLAMA 3.2 was pre-trained on up to 9 trillion high quality tokens.
+
+# What should Fijik be used for?
+Fijik 
 
 # Uploaded  model
 
 - **Developed by:** Pinkstack
-- **License:** apache-2.0
+- **License:** Llama 3.2 community license
 - **Finetuned from model :** Pinkstack/Fijik-6b-v1
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
-
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+This llama model was trained with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.