Text Classification
Transformers
Safetensors
PyTorch
English
ticket_gpt
feature-extraction
gpt2
custom-architecture
tiktoken
custom_code
Instructions to use FarhanAK128/TicketClassificationGPT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FarhanAK128/TicketClassificationGPT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FarhanAK128/TicketClassificationGPT", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("FarhanAK128/TicketClassificationGPT", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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### ๐ Model Description
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- **Developed by:** Farhan Ali Khan
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- **Model type:** GPT-2โ
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- **Base architecture:** GPT-2 (OpenAI)
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- **Framework:** PyTorch
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- **Task:** Text Classification
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- **Number of classes:** 8
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- **Language:** English
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- **License:** MIT
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- **Finetuned from model:** OpenAI GPT-2
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### ๐ Classification Labels
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### ๐ Model Description
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- **Developed by:** Farhan Ali Khan
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- **Model type:** GPT-2โlike text classification model
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- **Framework:** PyTorch
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- **Task:** Text Classification
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- **Number of classes:** 8
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- **Language:** English
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- **License:** MIT
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### ๐ Classification Labels
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