Update README.md

README.md

@@ -12,19 +12,19 @@ pipeline_tag: text-generation
 
 # Model Card for xlstm-7b-instruct-phase-2
 
-This model is a fine-tuned version of [ethicalabs/xLSTM-7b-Instruct](https://huggingface.co/ethicalabs/xLSTM-7b-Instruct).
-It has been trained using [TRL](https://github.com/huggingface/trl).
+This model is a fine-tuned version of [ethicalabs/xLSTM-7b-Instruct](https://huggingface.co/ethicalabs/xLSTM-7b-Instruct) for task alignment.
 
-## Quick start
+It has been trained using [TRL](https://github.com/huggingface/trl) using SFT on assistant-only tokens.
+
+The `k_proj` and `v_proj` matrices have been frozen to isolate and preserve the model's pre-trained knowledge base.
+
+This fine-tuning focused only on the `q_proj` (query) and FFN matrices, adapting the model's reasoning and query-retrieval mechanisms without overwriting its core, frozen knowledge.
 
-```python
-from transformers import pipeline
+This experiment was designed to test the hypothesis that the model's reasoning capabilities (`q_proj`) could be specialized for math/code while its knowledge (`k_proj`, `v_proj`) remained intact.
+
+## Quick start
 
-question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
-generator = pipeline("text-generation", model="None", device="cuda")
-output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
-print(output["generated_text"])
-```
+Work in Progress!
 
 ## Training procedure