Some minor readme fixes (#1)

- Some minor readme fixes (5ae3eec6fee052d4155f2969952bc22cdb293ddc)


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

README.md

@@ -37,22 +37,22 @@ pipeline_tag: image-text-to-text
 
 # Mistral-Small-3.2-24B-Instruct-2506
 
-Mistral-Small-3.2-24B-Instruct-2506 is a minor update of [Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Base-2503).
+Mistral-Small-3.2-24B-Instruct-2506 is a minor update of [Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503).
 
 Small-3.2 improves in the following categories:
 - **Instruction following**: Small-3.2 is better at following precise instructions
 - **Repetition errors**: Small-3.2 produces less infinite generations or repetitive answers
 - **Function calling**: Small-3.2's function calling template is more robust (see [here](https://github.com/mistralai/mistral-common/blob/535b4d0a0fc94674ea17db6cf8dc2079b81cbcfa/src/mistral_common/tokens/tokenizers/instruct.py#L778) and [examples](#function-calling))
 
-In all other categories Small-3.2 should match or slightly improve compared to [Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Base-2503).
+In all other categories Small-3.2 should match or slightly improve compared to [Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503).
 
 ## Key Features
-- same as [Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Base-2503#key-features)
+- same as [Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503#key-features)
 
 ## Benchmark Results
 
-We compare Mistral-Small-3.2-24B to [Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Base-2503).
-For more comparison against other models of similar size, please check [Mistral-Small-3.1's Benchmarks'](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Base-2503#benchmark-results)
+We compare Mistral-Small-3.2-24B to [Mistral-Small-3.1-24B-Instruct-2503](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503).
+For more comparison against other models of similar size, please check [Mistral-Small-3.1's Benchmarks'](https://huggingface.co/mistralai/Mistral-Small-3.1-24B-Instruct-2503#benchmark-results)
 
 ### Text 
 
@@ -65,7 +65,7 @@ For more comparison against other models of similar size, please check [Mistral-
 
 #### Infinite Generations
 
-Small 3.2 reduces infitine generations by 2x on challenging, long and repetitive prompts.
+Small 3.2 reduces infinite generations by 2x on challenging, long and repetitive prompts.
 
 | Model | Infinite Generations (Internal; Lower is better) |
 |-------|-------|
@@ -95,7 +95,7 @@ The model can be used with the following frameworks;
 
 **Note 1**: We recommend using a relatively low temperature, such as `temperature=0.15`.
 
-**Note 2**: Make sure to add a system prompt to the model to best tailer it for your needs. If you want to use the model as a general assistant, we recommend to use the one provided in the [SYSTEM_PROMPT.txt](https://huggingface.co/mistralai/Mistral-Small-3.2-24B-Instruct-2506/blob/main/SYSTEM_PROMPT.txt) file.
+**Note 2**: Make sure to add a system prompt to the model to best tailor it to your needs. If you want to use the model as a general assistant, we recommend to use the one provided in the [SYSTEM_PROMPT.txt](https://huggingface.co/mistralai/Mistral-Small-3.2-24B-Instruct-2506/blob/main/SYSTEM_PROMPT.txt) file.
 
 ### vLLM (recommended)
 
@@ -120,7 +120,7 @@ You can also make use of a ready-to-go [docker image](https://github.com/vllm-pr
 
 #### Serve
 
-We recommand that you use Mistral-Small-3.2-24B-Instruct-2506 in a server/client setting. 
+We recommend that you use Mistral-Small-3.2-24B-Instruct-2506 in a server/client setting. 
 
 1. Spin up a server:
 
@@ -136,7 +136,7 @@ vllm serve mistralai/Mistral-Small-3.2-24B-Instruct-2506 --tokenizer_mode mistra
 
 #### Vision reasoning
 
-Take leverage of the vision capabilities of Mistral-Small-3.2-24B-Instruct-2506 to take the best choice given a scenario, go catch them all !
+Leverage the vision capabilities of Mistral-Small-3.2-24B-Instruct-2506 to make the best choice given a scenario, go catch them all !
 
 <details>
   <summary>Python snippet</summary>