Update README.md
Browse files
README.md
CHANGED
@@ -1,28 +1,25 @@
|
|
1 |
---
|
2 |
language:
|
3 |
-
-
|
4 |
license: apache-2.0
|
5 |
base_model: mistralai/Mistral-7B-Instruct-v0.2
|
6 |
datasets:
|
7 |
- Antonio88/TaliStran-DataSet
|
8 |
---
|
9 |
|
10 |
-
|
11 |
-
|
12 |
![image/png](https://cdn-uploads.huggingface.co/production/uploads/644fc68af8b353c9491785d8/ARiB2V3Zgj1b7b26lvnWM.png)
|
13 |
|
14 |
|
15 |
|
16 |
-
TaliStran-7B-beta-V.1:
|
17 |
-
|
18 |
-
TaliStran è un modello di lingua italiana, sviluppato sfruttando la potenza di Mistral 7B Instruct v0.2. Questo modello è stato specificamente addestrato per comprendere e interagire in italiano, offrendo risposte coerenti a domande poste in questa lingua.
|
19 |
|
20 |
-
|
21 |
-
Addestramento: TaliStran è stato addestrato su un piccolo dataset selezionato di circa 500 domande e risposte, garantendo una preparazione mirata alla comprensione e alla generazione di testo in italiano.
|
22 |
|
23 |
-
|
|
|
24 |
|
|
|
25 |
|
26 |
-
|
27 |
|
28 |
-
|
|
|
1 |
---
|
2 |
language:
|
3 |
+
- en
|
4 |
license: apache-2.0
|
5 |
base_model: mistralai/Mistral-7B-Instruct-v0.2
|
6 |
datasets:
|
7 |
- Antonio88/TaliStran-DataSet
|
8 |
---
|
9 |
|
|
|
|
|
10 |
![image/png](https://cdn-uploads.huggingface.co/production/uploads/644fc68af8b353c9491785d8/ARiB2V3Zgj1b7b26lvnWM.png)
|
11 |
|
12 |
|
13 |
|
14 |
+
TaliStran-7B-beta-V.1: The Italian Language Model
|
|
|
|
|
15 |
|
16 |
+
TaliStran is a model developed by leveraging the power of Mistral 7B Instruct v0.2. This model has been specifically trained to understand and interact in Italian, providing coherent responses to questions asked in this language.
|
|
|
17 |
|
18 |
+
Main Features:
|
19 |
+
Training: TaliStran was trained on a selected small dataset of about 500 questions and answers, ensuring targeted preparation for understanding and generating text in Italian.
|
20 |
|
21 |
+
Training Efficiency: The training process was carried out using Google Colab, utilizing an A100 graphics card, which allowed the preparation to be completed efficiently and with limited resources.
|
22 |
|
23 |
+
Model in Test
|
24 |
|
25 |
+
there will be continuous improvements
|