Update README.md

README.md

@@ -16,17 +16,17 @@ pipeline_tag: text-generation
 
 The **Llama-3.1-8B-Adapted** collection of large language models (LLMs), is a collection of adapted generative models in 8B (text in/text out), adapted models from **Llama-3.1-8B**.
 
-*Llama-3.1-8B-Italian-FVT* is a continually trained Mistral model, after tokenizer substitution.
+*Llama-3.1-8B-Italian-FVT* is a continually trained Llama model, after tokenizer substitution.
 
 The tokenizer of this model after adaptation is the same as [Minverva-3B](https://huggingface.co/sapienzanlp/Minerva-3B-base-v1.0).
 
 **Model developer:** SapienzaNLP, ISTI-CNR, ILC-CNR
 
-**Model Architecture:** Mistral-7B-v0.1-Adapted is an auto-regressive language model that uses an optimized transformer architecture.
+**Model Architecture:** Llama-3.1-8B-Adapted is an auto-regressive language model that uses an optimized transformer architecture.
 
 ## Data used for the adaptation
 
-The **Mistral-7B-v0.1-Adapted** model was trained on a collection of Italian and English data extracted from [CulturaX](https://huggingface.co/datasets/uonlp/CulturaX).
+The **Llama-3.1-8B-Adapted** model was trained on a collection of Italian and English data extracted from [CulturaX](https://huggingface.co/datasets/uonlp/CulturaX).
 The data was extracted to be skewed toward Italian language with a ratio of one over four. Extracting the first 9B tokens from the Italian part of CulturaX and the first 3B tokens from the English part of CulturaX.
 
 
@@ -49,6 +49,8 @@ pipeline = transformers.pipeline(
 pipeline("Cosa si può fare in una bella giornata di sole?")
 ```
 
+Code: https://github.com/SapienzaNLP/sava
+
 ## Citation
 
 If you use any part of this work, please consider citing the paper as follows: