gsar78 commited on
Commit
b7a021c
·
verified ·
1 Parent(s): 3065ebf

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +7 -2
README.md CHANGED
@@ -11,7 +11,7 @@ pipeline_tag: text-classification
11
 
12
  ## Model Description
13
 
14
- This model is designed for sentiment analysis of Greek texts.
15
 
16
  It classifies the sentiment of a given Greek sentence or paragraph into positive, negative, or neutral and also provides the confidence score of each prediction.
17
 
@@ -23,7 +23,7 @@ The model is the result of meticulous craftsmanship, carefully handcrafted and f
23
 
24
  ## Model Details
25
 
26
- - **Model Name:** HellenicSentimentAI
27
  - **Model Version:** 1.0
28
  - **Language:** Multilingual
29
  - **Framework:** Transformers (Hugging Face)
@@ -32,6 +32,11 @@ The model is the result of meticulous craftsmanship, carefully handcrafted and f
32
  - **Fine-tuning Data:** The model was trained on a custom, curated multilingual dataset, comprising human-handpicked reviews from products, places, and restaurants, with a specific emphasis on Greek language texts.
33
 
34
 
 
 
 
 
 
35
  ## Usage:
36
 
37
  (Notice: There is no need for a GPU when inference the model)
 
11
 
12
  ## Model Description
13
 
14
+ This model is designed for sentiment analysis of Greek texts.
15
 
16
  It classifies the sentiment of a given Greek sentence or paragraph into positive, negative, or neutral and also provides the confidence score of each prediction.
17
 
 
23
 
24
  ## Model Details
25
 
26
+ - **Model Name:** Hellenic Sentiment AI
27
  - **Model Version:** 1.0
28
  - **Language:** Multilingual
29
  - **Framework:** Transformers (Hugging Face)
 
32
  - **Fine-tuning Data:** The model was trained on a custom, curated multilingual dataset, comprising human-handpicked reviews from products, places, and restaurants, with a specific emphasis on Greek language texts.
33
 
34
 
35
+ ## Production readiness
36
+
37
+ This model is a production-grade sentiment analysis solution, carefully designed and trained to deliver high-performance results in downstream applications. With its robust architecture and rigorous testing, it is ready to be deployed in real-world scenarios, providing accurate and reliable sentiment analysis capabilities for a wide range of use cases.
38
+
39
+
40
  ## Usage:
41
 
42
  (Notice: There is no need for a GPU when inference the model)