docs: fix typos and clarify README

README.md

@@ -8,7 +8,7 @@ This repo is a full-stack implementation of an LLM like ChatGPT in a single, cle
 
 ## Talk to it
 
-To get a sense of the endpoint of this repo, you can currently find [nanochat d32](https://github.com/karpathy/nanochat/discussions/8) hosted on [nanochat.karpathy.ai](https://nanochat.karpathy.ai/). "d32" means that this model has 32 layers in the Transformer neural network. This model has 1.9 billion parameters, it was trained on 38 billion tokens by simply running the single script [run1000.sh](run1000.sh), and the total cost of training was ~$800 (about 33 hours training time on 8XH100 GPU node). While today this is enough to outperform GPT-2 of 2019, it falls dramatically short of moden Large Language Models like GPT-5. When talking to these micro models, you'll see that they make a lot of mistakes, they are a little bit naive and silly and they hallucinate a ton, a bit like children. It's kind of amusing. But what makes nanochat unique is that it is fully yours - fully configurable, tweakable, hackable, and trained by you from start to end. To train and talk to your own, we turn to...
+To get a sense of the endpoint of this repo, you can currently find [nanochat d32](https://github.com/karpathy/nanochat/discussions/8) hosted on [nanochat.karpathy.ai](https://nanochat.karpathy.ai/). "d32" means that this model has 32 layers in the Transformer neural network. This model has 1.9 billion parameters, it was trained on 38 billion tokens by simply running the single script [run1000.sh](run1000.sh), and the total cost of training was ~$800 (about 33 hours training time on 8XH100 GPU node). While today this is enough to outperform GPT-2 of 2019, it falls dramatically short of modern Large Language Models like GPT-5. When talking to these micro models, you'll see that they make a lot of mistakes, they are a little bit naive and silly and they hallucinate a ton, a bit like children. It's kind of amusing. But what makes nanochat unique is that it is fully yours - fully configurable, tweakable, hackable, and trained by you from start to end. To train and talk to your own, we turn to...
 
 ## Quick start
 
@@ -95,7 +95,7 @@ And a bit more about computing environments that will run nanochat:
 
 ## Running on CPU / MPS
 
-nanochat cn be run on CPU or on MPS (if you're on Macbook), and will automatically try to detect what device is best to run on. You're not going to get too far without GPUs, but at least you'll be able to run the code paths and maybe train a tiny LLM with some patience. For an example of how to make all the run commands much smaller (feel free to tune!), you can refer to [dev/runcpu.sh](dev/runcpu.sh) file. You'll see that I'm essentially restricting all scripts to train smaller models, to run for shorter number of iterations, etc. This functionality is new, slightly gnarly (touched a lot of code), and was merged in this [CPU|MPS PR](https://github.com/karpathy/nanochat/pull/88) on Oct 21, 2025.
+nanochat can be run on CPU or on MPS (if you're on Macbook), and will automatically try to detect what device is best to run on. You're not going to get too far without GPUs, but at least you'll be able to run the code paths and maybe train a tiny LLM with some patience. For an example of how to make all the run commands much smaller (feel free to tune!), you can refer to [dev/runcpu.sh](dev/runcpu.sh) file. You'll see that I'm essentially restricting all scripts to train smaller models, to run for shorter number of iterations, etc. This functionality is new, slightly gnarly (touched a lot of code), and was merged in this [CPU|MPS PR](https://github.com/karpathy/nanochat/pull/88) on Oct 21, 2025.
 
 ## Customization
 
@@ -181,7 +181,7 @@ python -m pytest tests/test_rustbpe.py -v -s
 │   ├── gsm8k.py                    # 8K Grade School Math questions
 │   ├── humaneval.py                # Misnomer; Simple Python coding task
 │   ├── mmlu.py                     # Multiple choice questions, broad topics
-│   ├── smoltalk.py                 # Conglomarate dataset of SmolTalk from HF
+│   ├── smoltalk.py                 # Conglomerate dataset of SmolTalk from HF
 │   └── spellingbee.py              # Task teaching model to spell/count letters
 ├── tests
 │   └── test_rustbpe.py
@@ -192,7 +192,7 @@ python -m pytest tests/test_rustbpe.py -v -s
 
 nanochat is nowhere finished. The goal is to improve the state of the art in micro models that are accessible to work with end to end on budgets of < $1000 dollars. Accessibility is about overall cost but also about cognitive complexity - nanochat is not an exhaustively configurable LLM "framework"; there will be no giant configuration objects, model factories, or if-then-else monsters in the code base. It is a single, cohesive, minimal, readable, hackable, maximally-forkable "strong baseline" codebase designed to run start to end and produce a concrete ChatGPT clone and its report card.
 
-I am looking for someone to be the "nanochat repo czar" to help me manage the nanochat repo and its issues and PRs and be the first round of defense. Examples of work include merging simple fixes (docs, typos, clear and simple bugs etc.), rejecting vibe coded PRs, managing the Issues/PRs, doing brief "sanity check testing" of PRs on the two officially supported platforms (Linux/GPU and Macbook), organizing information into brief updates and highlights for me. We'd be in touch on DMs on Discord or X or whatever is easiest. For your services to the repo you will be listed and linked to under acknowledgements as the nanochat repo czar. Position is at-will so you can contribute for a while and then "resign" at any time later, totally ok and thank you for your help, just me know. Apply via DM to me on X, thank you!
+I am looking for someone to be the "nanochat repo czar" to help me manage the nanochat repo and its issues and PRs and be the first round of defense. Examples of work include merging simple fixes (docs, typos, clear and simple bugs etc.), rejecting vibe coded PRs, managing the Issues/PRs, doing brief "sanity check testing" of PRs on the two officially supported platforms (Linux/GPU and Macbook), organizing information into brief updates and highlights for me. We'd be in touch on DMs on Discord or X or whatever is easiest. For your services to the repo you will be listed and linked to under acknowledgements as the nanochat repo czar. Position is at-will so you can contribute for a while and then "resign" at any time later, totally ok and thank you for your help, just let me know. Apply via DM to me on X, thank you!
 
 ## Acknowledgements