Update README.md

## Model Overview
This model is a fine-tuned KeyBERT model for extracting keywords and phrases from a given text. It's based on the `all-MiniLM-L6-v2` transformer model from Sentence Transformers, making it efficient for SEO keyword optimization tasks.

## Intended Use
This model is ideal for:
- Extracting top keywords for SEO optimization
- Improving search engine rankings through keyword analysis
- Analyzing text to find important phrases in articles, blogs, or marketing content

## Input Data
The model expects plain text as input. You can use sentences, paragraphs, or entire articles, and the model will return a list of relevant keywords and keyphrases.

## Output
The output is a list of extracted keywords and keyphrases, ranked by their relevance to the input text. Each keyword/phrase is paired with a similarity score between 0 and 1, indicating its importance.

## How to Use
Here’s an example of how to use the model to extract keywords:

```python
from keybert import KeyBERT
from sentence_transformers import SentenceTransformer

# Load the model
sentence_model = SentenceTransformer('all-MiniLM-L6-v2')
model = KeyBERT(sentence_model)

# Sample text
text = "Digital marketing and artificial intelligence are transforming the way marketing content is created."

# Extract keywords
keywords = model.extract_keywords(text, keyphrase_ngram_range=(1, 3), top_n=5)

print(keywords)

## Training Process
The model was fine-tuned using the KeyBERT library with the `all-MiniLM-L6-v2` transformer from Sentence Transformers. The training process focused on optimizing keyword extraction for SEO applications.

## Limitations
- The model performs best on English text. Other languages may yield less accurate results.
- It may not perform well on very short texts (less than a sentence) or texts without much variability.

## Credits
This model is built using:
- [KeyBERT](https://github.com/MaartenGr/KeyBERT) for keyword extraction
- [Sentence Transformers](https://www.sbert.net/) for the underlying language model

README.md

@@ -1,3 +1,12 @@
----
-license: mit
----
+---
+license: mit
+language:
+- en
+base_model:
+- sentence-transformers/all-MiniLM-L6-v2
+tags:
+- seo
+- nlp
+- keyword extraction
+- transformer
+---