Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use akaminer/trial-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use akaminer/trial-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="akaminer/trial-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("akaminer/trial-model") model = AutoModelForSequenceClassification.from_pretrained("akaminer/trial-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bccbdeb617257ea3b8a11f15c5e40a69397b7c3dbfbedc7978e3132ddda7655f
- Size of remote file:
- 4.6 kB
- SHA256:
- 9f111be0d702939b773d8e1857a33c9bbfac16796cfe001b29ccc43b13986194
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