Update README.md

README.md

@@ -5,47 +5,47 @@ tags:
 - mixtral
 ---
 
-    # MetaModel_moe
+# MetaModel_moe
 
-    This model is a Mixure of Experts (MoE) made with [mergekit](https://github.com/cg123/mergekit) (mixtral branch). It uses the following base models:
-    * [gagan3012/MetaModel](https://huggingface.co/gagan3012/MetaModel)
-    * [jeonsworld/CarbonVillain-en-10.7B-v2](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v2)
-    * [jeonsworld/CarbonVillain-en-10.7B-v4](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v4)
-    * [TomGrc/FusionNet_linear](https://huggingface.co/TomGrc/FusionNet_linear)
+This model is a Mixure of Experts (MoE) made with [mergekit](https://github.com/cg123/mergekit) (mixtral branch). It uses the following base models:
+* [gagan3012/MetaModel](https://huggingface.co/gagan3012/MetaModel)
+* [jeonsworld/CarbonVillain-en-10.7B-v2](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v2)
+* [jeonsworld/CarbonVillain-en-10.7B-v4](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v4)
+* [TomGrc/FusionNet_linear](https://huggingface.co/TomGrc/FusionNet_linear)
 
-    ## 🧩 Configuration
+## 🧩 Configuration
 
-    ```yaml
+```yaml
 base_model: gagan3012/MetaModel
 gate_mode: hidden
 dtype: bfloat16
 experts:
-  - source_model: gagan3012/MetaModel
-  - source_model: jeonsworld/CarbonVillain-en-10.7B-v2
-  - source_model: jeonsworld/CarbonVillain-en-10.7B-v4
-  - source_model: TomGrc/FusionNet_linear
-    ```
-
-    ## 💻 Usage
-
-    ```python
-    !pip install -qU transformers bitsandbytes accelerate
-
-    from transformers import AutoTokenizer
-    import transformers
-    import torch
-
-    model = "gagan3012/MetaModel_moe"
-
-    tokenizer = AutoTokenizer.from_pretrained(model)
-    pipeline = transformers.pipeline(
-        "text-generation",
-        model=model,
-        model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
-    )
-
-    messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
-    prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-    outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
-    print(outputs[0]["generated_text"])
-    ```
+- source_model: gagan3012/MetaModel
+- source_model: jeonsworld/CarbonVillain-en-10.7B-v2
+- source_model: jeonsworld/CarbonVillain-en-10.7B-v4
+- source_model: TomGrc/FusionNet_linear
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers bitsandbytes accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "gagan3012/MetaModel_moe"
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
+)
+
+messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
+prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```