Update README.md

README.md

@@ -40,7 +40,7 @@ Here we host public weights for our biomedical language models. There are severa
 
 | Model      | Domain  | Type              | Details                                                     |
 |------------|---------|-------------------|-------------------------------------------------------------|
-| [Igea](https://huggingface.co/Detsutut/Igea-1B-v0.0.1) | Biomedical | CausalLM Pretrain | Small language model trained after [sapienzanlp/Minerva-1B-base-v1.0](https://huggingface.co/sapienzanlp/Minerva-1B-base-v1.0) with 28GB Pubmed abstracts. Two versions available: [350M params](https://huggingface.co/bmi-labmedinfo/Igea-350M-v0.0.1) and [1B params](https://huggingface.co/bmi-labmedinfo/Igea-1B-v0.0.1) (recommended) |
+| [Igea](https://huggingface.co/Detsutut/Igea-1B-v0.0.1) | Biomedical | CausalLM Pretrain | Small language model trained after [sapienzanlp/Minerva-1B-base-v1.0](https://huggingface.co/sapienzanlp/Minerva-1B-base-v1.0) with more than 5 billion biomedical words in Italian. Three versions available: [350M params](https://huggingface.co/bmi-labmedinfo/Igea-350M-v0.0.1), [1B params](https://huggingface.co/bmi-labmedinfo/Igea-1B-v0.0.1), and [3B params](https://huggingface.co/bmi-labmedinfo/Igea-3B-v0.0.1). Use the [quantized GGUF version](Detsutut/Igea-1B-v0.0.1-Q4_K_M-GGUF) for CPU-only, limited-hardware machines. |
 | [BioBIT](https://huggingface.co/bmi-labmedinfo/bioBIT) <sup>*</sup>| Biomedical | MaskedLM Pretrain | BERT model trained after [dbmdz/bert-base-italian-xxl-cased](https://huggingface.co/dbmdz/bert-base-italian-xxl-cased) with 28GB Pubmed abstracts (as in BioBERT) that have been translated from English into Italian using Neural Machine Translation (GNMT). |
 | [MedBIT](https://huggingface.co/bmi-labmedinfo/medBIT) <sup>*</sup>| Medical | MaskedLM Pretrain | BERT model trained after [BioBIT](https://huggingface.co/bmi-labmedinfo/bioBIT) with additional 100MB of medical textbook data without any regularization. |
 | [MedBIT-R3+](https://huggingface.co/bmi-labmedinfo/medBIT-r3-plus) (recommended) <sup>*</sup>| Medical | MaskedLM Pretrain | BERT model trained after [BioBIT](https://huggingface.co/bmi-labmedinfo/bioBIT) with additional 200MB of medical textbook data and web-crawled medical resources in Italian. Regularized with LLRD (.95), Mixout (.9), and Warmup (.02). |
@@ -48,8 +48,6 @@ Here we host public weights for our biomedical language models. There are severa
 <sup>*</sup> <small>model developed for the [Italian Neuroscience and Rehabilitation Network](https://www.reteneuroscienze.it/en/istituti-nazionali-virtuali/) in partnership with the Neuroinformatics Lab of IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy</small>
 
 
-Other models coming soon!
-
 ## Related Research Papers
 
 * *Buonocore T. M., Parimbelli E., Tibollo V., Napolitano C., Priori S., and Bellazzi R. (2023). A Rule-Free Approach for Cardiological Registry Filling from Italian Clinical Notes with Question Answering Transformers, Artificial Intelligence in Medicine: 21st International Conference on Artificial Intelligence in Medicine, AIME 2023. https://doi.org/10.1007/978-3-031-34344-5_19*