Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Noola/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Noola/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Noola/results")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Noola/results") model = AutoModelForSequenceClassification.from_pretrained("Noola/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| class CustomProvider: | |
| def __init__(self, model, tokenizer): | |
| self.model = model | |
| self.tokenizer = tokenizer | |
| def __call__(self, text): | |
| inputs = self.tokenizer(text, return_tensors="pt") | |
| outputs = self.model(**inputs) | |
| return outputs.logits.argmax(dim=-1).item() | |