Apply suggestions from code review

Co-authored-by: Rowena Jones <[email protected]>

Author: bene2k1

pages/generative-apis/troubleshooting/fixing-common-issues.mdx

@@ -17,12 +17,12 @@ Below are common issues that you may encounter when using Generative APIs, their
 
 ### Cause
 - You provided an input exceeding the maximum context window (also known as context length) for the model you are using. 
-- You provided a long input and requested a long input (in `max_completion_tokens` field), which added, exceeds the maximum context window of the model you are using. 
+- You provided a long input and requested a long input (in `max_completion_tokens` field), which added together, exceed the maximum context window of the model you are using. 
 
 ### Solution
 - Reduce your input size below what is [supported by the model](/generative-apis/reference-content/supported-models/). 
 - Use a model supporting longer context window values.
-- Use [Managed Inference](/managed-inference/), where context window can be increased for [several configuration with additional GPU vRAM](/managed-inference/reference-content/supported-models/). For instance, `llama-3.3-70b-instruct` model in `fp8` quantization can be served with:
+- Use [Managed Inference](/managed-inference/), where the context window can be increased for [several configurations with additional GPU vRAM](/managed-inference/reference-content/supported-models/). For instance, `llama-3.3-70b-instruct` model in `fp8` quantization can be served with:
   - `15k` tokens context window on `H100` instances
   - `128k` tokens context window on `H100-2` instances.
 
@@ -43,7 +43,7 @@ Below are common issues that you may encounter when using Generative APIs, their
 ## 416: Range Not Satisfiable - max_completion_tokens is limited for this model
 
 ### Cause
-- You provided `max_completion_tokens` value too high, that is not supported by the model you are using.
+- You provided a value for `max_completion_tokens` that is too high and not supported by the model you are using.
 
 ### Solution
 - Remove `max_completion_tokens` field from your request or client library, or reduce its value below what is [supported by the model](https://www.scaleway.com/en/docs/generative-apis/reference-content/supported-models/). 
@@ -60,12 +60,12 @@ Below are common issues that you may encounter when using Generative APIs, their
 - You provided `max_completion_tokens` value too high, that is not supported by the model you are using.
 
 ### Solution
-- Remove `max_completion_tokens` field from your request or client library, or reduce its value below what is [supported by the model](https://www.scaleway.com/en/docs/generative-apis/reference-content/supported-models/). 
+- Remove the `max_completion_tokens` field from your request or client library, or reduce its value below what is [supported by the model](https://www.scaleway.com/en/docs/generative-apis/reference-content/supported-models/). 
   - As an example, when using the [init_chat_model from Langchain](https://python.langchain.com/api_reference/_modules/langchain/chat_models/base.html#init_chat_model), you should edit the `max_tokens` value in the following configuration:
     ```python
     llm = init_chat_model("llama-3.3-70b-instruct", max_tokens="8000", model_provider="openai", base_url="https://api.scaleway.ai/v1", temperature=0.7)
     ```
-- Use a model supporting higher `max_completion_tokens` value.
+- Use a model supporting a higher `max_completion_tokens` value.
 - Use [Managed Inference](/managed-inference/), where these limits on completion tokens do not apply (your completion tokens amount will still be limited by the maximum context window supported by the model). 
 
 ## 429: Too Many Requests - You exceeded your current quota of requests/tokens per minute