Update README.md

README.md

@@ -22,7 +22,7 @@ The evaluation consists in a team project (3-5 people). The choice of the subjec
 - Obviously, the project must be highly related with NLP and especially with the notions we will cover in the course
 - You can only use open-source LLM that _you serve yourself_. In other words, no API / ChatGPT-like must be used, except for final comparison with your model.
 - You must identify and address a <ins>challenging</ins> problem (e.g. not only _can a LLM do X?_, but _can a LLM <ins>that runs on a CPU</ins> do X?_, or _can I make a LLM <ins>better</ins> at X?_)
-- It must be reasonably doable: you will not be able to fine-tune (even to use) a 405B parameters model, or to train a model from scratch. That's fine, there are a lot of smaller models that should be good enough, like [the Pythia models](https://huggingface.co/collections/EleutherAI/pythia-scaling-suite-64fb5dfa8c21ebb3db7ad2e1), [TinyLLama](https://huggingface.co/collections/TinyLlama/tinyllama-11b-v1-660bb5bfabd8bd25eebbb1ef) or the 1B parameter [OLMo](https://huggingface.co/collections/allenai/olmo-suite-65aeaae8fe5b6b2122b46778).
+- It must be reasonably doable: you will not be able to fine-tune (even to use) a 405B parameters model, or to train a model from scratch. That's fine, there are a lot of smaller models that should be good enough, like [the Pythia models](https://huggingface.co/collections/EleutherAI/pythia-scaling-suite-64fb5dfa8c21ebb3db7ad2e1), [TinyLLama](https://huggingface.co/collections/TinyLlama/tinyllama-11b-v1-660bb5bfabd8bd25eebbb1ef), the 1B parameter [OLMo](https://huggingface.co/collections/allenai/olmo-suite-65aeaae8fe5b6b2122b46778), or the small models from the [Llama3.2 suite](https://huggingface.co/collections/meta-llama/llama-32-66f448ffc8c32f949b04c8cf).
 
 :alarm_clock: The project follows 3 deadlines: