Downloads · 30 days
9
24% of all-time downloads
pe-llm-0
kolkata97/pe-llm-0
pe-llm-0 is a text classification model from kolkata97. Use it when you need a label for a piece of text. It is set up for transformers.
- Problem type: Multi-class Classification - Model ID: pe-llm-0.1 - CO2 Emissions (in grams): 0.0221
All-time downloads
38
Public
Parameters
110M
880 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin440 MB · 50%
Parameter types
How the weights are stored.
F32110M · 100%
Try a prompt
Model card
From the Hugging Face model README
Model Trained
- Problem type: Multi-class Classification
- Model ID: pe-llm-0.1
- CO2 Emissions (in grams): 0.0221
Validation Metrics
- Loss: 0.841
- Accuracy: 0.761
- Macro F1: 0.644
- Micro F1: 0.761
- Weighted F1: 0.750
- Macro Precision: 0.679
- Micro Precision: 0.761
- Weighted Precision: 0.748
- Macro Recall: 0.635
- Micro Recall: 0.761
- Weighted Recall: 0.761
Usage
You can use cURL to access this model:
$ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"inputs": "I love AutoTrain"}' https://api-inference.huggingface.co/models/kolkata97/autotrain-pe-llm-0.6-89942144050
Or Python API:
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model = AutoModelForSequenceClassification.from_pretrained("kolkata97/autotrain-pe-llm-0.6-89942144050", use_auth_token=True)
tokenizer = AutoTokenizer.from_pretrained("kolkata97/autotrain-pe-llm-0.6-89942144050", use_auth_token=True)
inputs = tokenizer("I love AutoTrain", return_tensors="pt")
outputs = model(**inputs)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- Languages
- it
- Created
- Sep 18, 2023
- Updated
- Feb 6, 2024