Text Classification
Transformers
Safetensors
English
deberta-v2
code
openmp
hpc
compilers
parallel-computing
static-analysis
Eval Results (legacy)
text-embeddings-inference
Instructions to use Harshagrawal526/autopragma with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Harshagrawal526/autopragma with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Harshagrawal526/autopragma")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Harshagrawal526/autopragma") model = AutoModelForSequenceClassification.from_pretrained("Harshagrawal526/autopragma", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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