Update README.md

README.md

@@ -566,8 +566,7 @@ language:
 
 # Refact-1.6B
 
-Finally, the model we started training with our blog post
-[Applying Recent Innovations](https://refact.ai/blog/2023/applying-recent-innovations-to-train-model/) is ready 🎉
+Finally, the model we started training with our [blog post](https://refact.ai/blog/2023/applying-recent-innovations-to-train-model/) is ready 🎉
 
 After fine-tuning on generated data, it beats Replit 3b, Stability Code 3b and many other models. It almost beats
 StarCoder ten times the size!
@@ -614,7 +613,7 @@ Filtering is the key to success of this model:
 The text to code proportion was 50:50, model trained for 1.2T tokens. 
 
 We don't release the base model, because its Fill-in-the-Middle (FIM) capability likes to repeat itself too much, so
-its practical use is limited. But if you still want it, write us a message on discord.
+its practical use is limited. But if you still want it, write us a message on Discord.
 
 
 # Finetuning
@@ -633,7 +632,7 @@ The former is likely finished, so the model tries to come up with a suggestion t
 You are likely to have half-written code as you work on it, there is no single addition that can repair it
 fully.
 
-In practice, model needs to have a tendency to stop after a couple of lines added, and sometimes don't write
+In practice, model needs to have a tendency to stop after a couple of lines are added, and sometimes don't write
 anything at all. We found that just giving it empty completions, single line completions, multiline
 completions that end with a smaller text indent or at least a newline -- makes it much more usable. This data
 was used as the rest 85% of the finetune dataset.