Text Classification
Transformers
Safetensors
English
qwen2
text-generation
LLM
classification
instruction-tuned
multi-label
qwen
text-embeddings-inference
Instructions to use BenchHub/BenchHub-Cat-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BenchHub/BenchHub-Cat-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="BenchHub/BenchHub-Cat-7b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("BenchHub/BenchHub-Cat-7b") model = AutoModelForCausalLM.from_pretrained("BenchHub/BenchHub-Cat-7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# BenchHub-Cat-7b
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**BenchHub-Cat-7b** is a category classification model based on **Qwen2.5-7B**, fine-tuned to assign natural language queries to structured category triplets: `(subject, skill, target)`.
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license: apache-2.0
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# BenchHub-Cat-7b
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**BenchHub-Cat-7b** is a category classification model based on **Qwen2.5-7B**, fine-tuned to assign natural language queries to structured category triplets: `(subject, skill, target)`.
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