Update README.md
Browse files
README.md
CHANGED
@@ -51,6 +51,7 @@ tags:
|
|
51 |
|
52 |
|
53 |
# NEWS!
|
|
|
54 |
|
55 |
- 2025/7: We’ve just released ModernFinBERT, a model we’ve been working on for a while. It’s built on the ModernBERT architecture and trained on a mix of real and synthetic data, with LLM-based label correction applied to public datasets to fix human annotation errors.
|
56 |
It’s performing well across a range of benchmarks — in some cases improving accuracy by up to 48% over existing models like FinBERT.
|
@@ -59,6 +60,20 @@ You can check it out here on Hugging Face:
|
|
59 |
|
60 |
- 2024/12: We are excited to introduce a multilingual sentiment model! Now you can analyze sentiment across multiple languages, enhancing your global reach.
|
61 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
62 |
## Model Details
|
63 |
- `Model Name:` tabularisai/multilingual-sentiment-analysis
|
64 |
- `Base Model:` distilbert/distilbert-base-multilingual-cased
|
@@ -76,6 +91,7 @@ You can check it out here on Hugging Face:
|
|
76 |
|
77 |
> If you wish to use this model for commercial purposes, please obtain a license by contacting: [email protected]
|
78 |
|
|
|
79 |
## Model Description
|
80 |
|
81 |
This model is a fine-tuned version of `distilbert/distilbert-base-multilingual-cased` for multilingual sentiment analysis. It leverages synthetic data from multiple sources to achieve robust performance across different languages and cultural contexts.
|
|
|
51 |
|
52 |
|
53 |
# NEWS!
|
54 |
+
- 2025/8: API for our model! Please see below!
|
55 |
|
56 |
- 2025/7: We’ve just released ModernFinBERT, a model we’ve been working on for a while. It’s built on the ModernBERT architecture and trained on a mix of real and synthetic data, with LLM-based label correction applied to public datasets to fix human annotation errors.
|
57 |
It’s performing well across a range of benchmarks — in some cases improving accuracy by up to 48% over existing models like FinBERT.
|
|
|
60 |
|
61 |
- 2024/12: We are excited to introduce a multilingual sentiment model! Now you can analyze sentiment across multiple languages, enhancing your global reach.
|
62 |
|
63 |
+
|
64 |
+
## 🔌 Hosted API
|
65 |
+
|
66 |
+
We provide a hosted inference API:
|
67 |
+
|
68 |
+
**Example request body:**
|
69 |
+
|
70 |
+
```json
|
71 |
+
curl -X POST https://api.tabularis.ai/ \
|
72 |
+
-H "Content-Type: application/json" \
|
73 |
+
-d '{"text":"I love the design","return_all_scores":false}'
|
74 |
+
|
75 |
+
```
|
76 |
+
|
77 |
## Model Details
|
78 |
- `Model Name:` tabularisai/multilingual-sentiment-analysis
|
79 |
- `Base Model:` distilbert/distilbert-base-multilingual-cased
|
|
|
91 |
|
92 |
> If you wish to use this model for commercial purposes, please obtain a license by contacting: [email protected]
|
93 |
|
94 |
+
|
95 |
## Model Description
|
96 |
|
97 |
This model is a fine-tuned version of `distilbert/distilbert-base-multilingual-cased` for multilingual sentiment analysis. It leverages synthetic data from multiple sources to achieve robust performance across different languages and cultural contexts.
|