Text Classification
Transformers
ONNX
Safetensors
English
roberta
code
programming-language
code-classification
text-embeddings-inference
Instructions to use philomath-1209/programming-language-identification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philomath-1209/programming-language-identification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philomath-1209/programming-language-identification")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philomath-1209/programming-language-identification") model = AutoModelForSequenceClassification.from_pretrained("philomath-1209/programming-language-identification") - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, TextClassificationPipeline
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model_name = '
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loaded_tokenizer = AutoTokenizer.from_pretrained(model_name)
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loaded_model = AutoModelForSequenceClassification.from_pretrained(model_name)
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```python
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, TextClassificationPipeline
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model_name = 'philomath-1209/programming-language-identification'
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loaded_tokenizer = AutoTokenizer.from_pretrained(model_name)
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loaded_model = AutoModelForSequenceClassification.from_pretrained(model_name)
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