Instructions to use FuriouslyAsleep/markingMultiClass with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FuriouslyAsleep/markingMultiClass with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FuriouslyAsleep/markingMultiClass")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FuriouslyAsleep/markingMultiClass") model = AutoModelForSequenceClassification.from_pretrained("FuriouslyAsleep/markingMultiClass", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| tags: autonlp | |
| language: en | |
| widget: | |
| - text: "I love AutoNLP 🤗" | |
| datasets: | |
| - FuriouslyAsleep/autotrain-data-markingClassifier | |
| co2_eq_emissions: 0.5712537632313806 | |
| # Model Trained Using AutoNLP | |
| - Problem type: Multi-class Classification | |
| - Model ID: 661319476 | |
| - CO2 Emissions (in grams): 0.5712537632313806 | |
| ## Validation Metrics | |
| - Loss: 0.859619140625 | |
| - Accuracy: 0.8 | |
| - Macro F1: 0.6 | |
| - Micro F1: 0.8000000000000002 | |
| - Weighted F1: 0.72 | |
| - Macro Precision: 0.5555555555555555 | |
| - Micro Precision: 0.8 | |
| - Weighted Precision: 0.6666666666666666 | |
| - Macro Recall: 0.6666666666666666 | |
| - Micro Recall: 0.8 | |
| - Weighted Recall: 0.8 | |
| ## 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 AutoNLP"}' https://api-inference.huggingface.co/models/FuriouslyAsleep/autonlp-markingClassifier-661319476 | |
| ``` | |
| Or Python API: | |
| ``` | |
| from transformers import AutoModelForSequenceClassification, AutoTokenizer | |
| model = AutoModelForSequenceClassification.from_pretrained("FuriouslyAsleep/autonlp-markingClassifier-661319476", use_auth_token=True) | |
| tokenizer = AutoTokenizer.from_pretrained("FuriouslyAsleep/autonlp-markingClassifier-661319476", use_auth_token=True) | |
| inputs = tokenizer("I love AutoNLP", return_tensors="pt") | |
| outputs = model(**inputs) | |
| ``` |