nijatzeynalov
commited on
Commit
•
63031ab
1
Parent(s):
b6682f6
Upload README.md with huggingface_hub
Browse files
README.md
ADDED
@@ -0,0 +1,24 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
{}
|
3 |
+
---
|
4 |
+
### Gym Membership Upgrades
|
5 |
+
|
6 |
+
**Description:** Classify member feedback to identify potential areas of improvement and opportunities for upselling premium services, such as personal training or nutrition counseling.
|
7 |
+
|
8 |
+
## How to Use
|
9 |
+
Here is how to use this model to classify text into different categories:
|
10 |
+
|
11 |
+
from transformers import AutoModelForSequenceClassification, AutoTokenizer
|
12 |
+
|
13 |
+
model_name = "interneuronai/gym_membership_upgrades_pegasus"
|
14 |
+
model = AutoModelForSequenceClassification.from_pretrained(model_name)
|
15 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
16 |
+
|
17 |
+
def classify_text(text):
|
18 |
+
inputs = tokenizer(text, return_tensors="pt", padding=True, truncation=True, max_length=512)
|
19 |
+
outputs = model(**inputs)
|
20 |
+
predictions = outputs.logits.argmax(-1)
|
21 |
+
return predictions.item()
|
22 |
+
|
23 |
+
text = "Your text here"
|
24 |
+
print("Category:", classify_text(text))
|