Fix: Typo in README.md

Fixes the spelling of achieving
Fix grammar for another sentence

README.md

@@ -20,7 +20,7 @@ Qwen1.5-MoE is a transformer-based MoE decoder-only language model pretrained on
 For more details, please refer to our [blog post](https://qwenlm.github.io/blog/qwen-moe/) and [GitHub repo](https://github.com/QwenLM/Qwen1.5).
 
 ## Model Details
-Qwen1.5-MoE employs Mixture of Experts (MoE) architecture, where the models are upcycled from dense language models. For instance, `Qwen1.5-MoE-A2.7B` is upcycled from `Qwen-1.8B`. It has 14.3B parameters in total and 2.7B activated parameters during runtime, while achieching comparable performance to `Qwen1.5-7B`, it only requires 25% of the training resources. We also observed that the inference speed is 1.74 times that of `Qwen1.5-7B`.
+Qwen1.5-MoE employs Mixture of Experts (MoE) architecture, where the models are upcycled from dense language models. For instance, `Qwen1.5-MoE-A2.7B` is upcycled from `Qwen-1.8B`. It has 14.3B parameters in total and 2.7B activated parameters during runtime, while achieving comparable performance to `Qwen1.5-7B`, it only requires 25% of the training resources. We also observed that the inference speed is 1.74 times that of `Qwen1.5-7B`.
 
 ## Training details
 We pretrained the models with a large amount of data, and we post-trained the models with both supervised finetuning and direct preference optimization. 
@@ -33,7 +33,7 @@ KeyError: 'qwen2_moe'.
 
 ## Quickstart
 
-Here provides a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
+Here we provide a code snippet with `apply_chat_template` to show you how to load the tokenizer and model and how to generate contents.
 
 ```python
 from transformers import AutoModelForCausalLM, AutoTokenizer