Apply suggestions from code review

Co-authored-by: Jessica <[email protected]>

Author: bene2k1

faq/managed-inference.mdx

@@ -22,7 +22,7 @@ All models are currently hosted in a secure data center located in Paris, France
 - **Managed Inference**: Allows deployment of curated or custom models with chosen quantization and instances, offering predictable throughput and enhanced security features like private network isolation and access control. Managed Inference is billed by hourly usage, whether provisioned capacity is receiving traffic or not.
 - **Generative APIs**: A serverless service providing access to pre-configured AI models via API, billed per token usage.
 
-## Where can I find information regarding the data, privacy and security policies applied to Scaleway's AI services?
+## Where can I find information regarding the data, privacy, and security policies applied to Scaleway's AI services?
 You can find detailed information regarding the policies applied to Scaleway's AI services in our [Data, privacy, and security for Scaleway's AI services](/managed-inference/reference-content/data-privacy-security-scaleway-ai-services/) documentation.
 
 ## Is Managed Inference compatible with Open AI APIs?
@@ -33,7 +33,7 @@ We are currently working on defining our SLAs for Managed Inference. We will pro
 
 ## What are the performance guarantees (vs. Generative APIs)?
 Managed Inference provides dedicated resources, ensuring predictable performance and lower latency compared to Generative APIs, which are a shared, serverless offering optimized for infrequent traffic with moderate peak loads. Managed Inference is ideal for workloads that require consistent response times, high availability, custom hardware configurations or generate extreme peak loads during a narrow period of time.
-Compared to Generative APIs, no usage quota are applied on the number of tokens per second generated, since the output is limited by the GPU Instances size and number of your Managed Inference Deployment.
+Compared to Generative APIs, no usage quota is applied to the number of tokens per second generated, since the output is limited by the GPU Instances size and number of your Managed Inference Deployment.
 
 ## What types of models can I deploy with Managed Inference?
 You can deploy a variety of models, including:
@@ -69,7 +69,7 @@ Yes, Managed Inference is designed for low-latency, high-throughput applications
 ## Can I use Managed Inference with other Scaleway services?
 Absolutely. Managed Inference integrates seamlessly with other Scaleway services, such as [Object Storage](/object-storage/quickstart/) for model hosting, [Kubernetes](/kubernetes/quickstart/) for containerized applications, and [Scaleway IAM](/iam/quickstart/) for access management.
 
-## Do model license apply when using Managed Inference?
-Yes, model licenses need to be complied with when using Managed Inference. Applicable licenses are available for [each model in our documentation](https://www.scaleway.com/en/docs/managed-inference/reference-content/).
+## Do model licenses apply when using Managed Inference?
+Yes, model licenses need to be complied with when using Managed Inference. Applicable licenses are available for [each model in our documentation](/managed-inference/reference-content/).
 - For models provided in the Scaleway catalog, you need to accept licenses (including potential EULA) before creating any Managed Inference deployment.
-- For custom models you choose to import on Scaleway, you are responsible to comply with model licenses (as with any software you choose to install on a GPU Instance for example).
+- For custom models you choose to import on Scaleway, you are responsible for complying with model licenses (as with any software you choose to install on a GPU Instance for example).