Update README.md

README.md

@@ -1,44 +1,37 @@
----
-base_model:
-- Or4cl3-1/Daedalus_1
-- microsoft/Phi-3-mini-4k-instruct
-tags:
-- merge
-- mergekit
-- lazymergekit
-- Or4cl3-1/Daedalus_1
-- microsoft/Phi-3-mini-4k-instruct
----
-
-# BathSalt-llama-3.1-slerp
-
-BathSalt-llama-3.1-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
-* [Or4cl3-1/Daedalus_1](https://huggingface.co/Or4cl3-1/Daedalus_1)
-* [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct)
-
-## 🧩 Configuration
-
-```yaml
-slices:
-  - sources:
-      - model: Or4cl3-1/Daedalus_1
-        layer_range: [0, 32]
-      - model: microsoft/Phi-3-mini-4k-instruct
-        layer_range: [0, 32]
-merge_method: slerp
-base_model: microsoft/Phi-3-mini-4k-instruct
-parameters:
-  t:
-    - filter: self_attn
-      value: [0, 0.5, 0.3, 0.7, 1]
-    - filter: mlp
-      value: [1, 0.5, 0.7, 0.3, 0]
-    - value: 0.5
-dtype: bfloat16
-```
-
-## 💻 Usage
 
+**Model Card**
+
+**Model Name:** BathSalt-1/daedalus-phi-3
+
+**Model Type:** Large Language Model
+
+**Description:** This model is a merge of the `Or4cl3-1/Daedalus_1` and `microsoft/Phi-3-mini-4k-instruct` models using the `LazyMergekit` library. It is designed for general-purpose natural language processing tasks.
+
+**Metadata:**
+
+* **License:** MIT License
+* **Language:** English
+* **Library:** Transformers
+* **Base Model:** microsoft/Phi-3-mini-4k-instruct
+* **Merge Method:** slerp
+* **Layer Range:** [0, 32]
+* **Parameters:**
+	+ t:
+		- filter: self_attn
+		- value: [0, 0.5, 0.3, 0.7, 1]
+		- filter: mlp
+		- value: [1, 0.5, 0.7, 0.3, 0]
+		- value: 0.5
+	+ dtype: bfloat16
+
+**Usage:**
+
+* **Tokenizer:** AutoTokenizer
+* **Model:** AutoModelForSeq2SeqLM
+* **Pipeline:** text-generation
+* **Device:** auto
+
+**Example Code:**
 ```python
 !pip install -qU transformers accelerate
 
@@ -46,7 +39,7 @@ from transformers import AutoTokenizer
 import transformers
 import torch
 
-model = "BathSalt-1/BathSalt-llama-3.1-slerp"
+model = "BathSalt-1/daedalus-phi-3"
 messages = [{"role": "user", "content": "What is a large language model?"}]
 
 tokenizer = AutoTokenizer.from_pretrained(model)