fixes

README.md

@@ -17,9 +17,7 @@ language:
 - en
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
-![image/png](./assets/gemma-2b-orpo.png)
+<img src="./assets/gemma-2b-orpo.png" width="300"></img>
 # gemma-2b-orpo
 
 This is an ORPO fine-tune of [google/gemma-2b](https://huggingface.co/google/gemma-2b) with
@@ -36,11 +34,13 @@ of SFT (Supervised Fine-Tuning) and Preference Alignment (usually performed with
 
 ### Nous
 
-gemma-2b-orpo performs well on Nous' benchmark suite (evaluation performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval)).
+gemma-2b-orpo performs well for its size on Nous' benchmark suite.
+
+(evaluation conducted using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval)).
 
 | Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
 |---|---:|---:|---:|---:|---:|
-| [anakin87/gemma-2b-orpo](https://huggingface.co/anakin87/gemma-2b-orpo) [📄](./assets/gemma-2b-orpo-Nous.md) | 39.45 | 23.76 | 58.25 | 44.47 | 31.32 |
+| [**anakin87/gemma-2b-orpo**](https://huggingface.co/anakin87/gemma-2b-orpo) [📄](./assets/gemma-2b-orpo-Nous.md) | **39.45** | 23.76 | 58.25 | 44.47 | 31.32 |
 | [mlabonne/Gemmalpaca-2B](https://huggingface.co/mlabonne/Gemmalpaca-2B) [📄](https://gist.github.com/mlabonne/4b638752fc3227df566f9562064cb864) | 38.39 | 24.48 | 51.22 | 47.02 | 30.85 |
 | [google/gemma-2b-it](https://huggingface.co/google/gemma-2b-it) [📄](https://gist.github.com/mlabonne/db0761e74175573292acf497da9e5d95) | 36.1 | 23.76 | 43.6 | 47.64 | 29.41 |
 | [google/gemma-2b](https://huggingface.co/google/gemma-2b) [📄](https://gist.github.com/mlabonne/7df1f238c515a5f63a750c8792cef59e) | 34.26 | 22.7 | 43.35 | 39.96 | 31.03 |
@@ -52,7 +52,8 @@ is a simplified version of [`argilla/dpo-mix-7k`](https://huggingface.co/dataset
 You can find more information [here](https://huggingface.co/alvarobartt/Mistral-7B-v0.1-ORPO#about-the-dataset).
 
 ## 🎮 Model in action
-### [📓 Examples: Chat and RAG using Haystack](./notebooks/usage.ipynb)
+### Usage notebook
+[📓 Chat and RAG using Haystack](./notebooks/usage.ipynb)
 ### Simple text generation with Transformers
 The model is small, so runs smoothly on Colab. *It is also fine to load the model using quantization*.
 ```python