Update README.md

README.md

@@ -5,6 +5,8 @@ language:
 license: apache-2.0
 pipeline_tag: text-generation
 library_name: transformers
+base_model:
+- mistralai/Mistral-7B-v0.1
 ---
 
 # Mistral-7B-v0.1-Italian-RANDOM
@@ -16,13 +18,13 @@ library_name: transformers
 
 The **Mistral-7B-v0.1-Adapted** collection of large language models (LLMs), is a collection of adapted generative models in 7B (text in/text out), adapted models from **Mistral-7B-Base-v0.1**.
 
-*Mistral-v0.1-Italian-RANDOM* is a continual trained mistral model, after tokenizer substitution.
+*Mistral-v0.1-Italian-RANDOM* is a continually trained mistral model, after tokenizer substitution.
 
 The tokenizer of this models after adaptation is the same of [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:** Mistral-7B-v0.1-Adapted are auto-regressive language models that uses an optimized transformer architecture.
 
 ## Data used for the adaptation
 
@@ -34,7 +36,7 @@ The data are extracted to be skewed toward Italian language with a ration of one
 
 You can run conversational inference using the Transformers pipeline abstraction or by leveraging the Auto classes with the generate() function.
 
-Make sure to update your transformers installation via pip install --upgrade transformers.
+Make sure to update your transformers installation via `pip install --upgrade transformers`.
 
 ```python
 import transformers
@@ -49,6 +51,8 @@ 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: