Transformers
PyTorch
English
t5
text2text-generation
keytotext
k2t
Keywords to Sentences
text-generation-inference
Instructions to use Apoorva/k2t-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Apoorva/k2t-test with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Apoorva/k2t-test") model = AutoModelForSeq2SeqLM.from_pretrained("Apoorva/k2t-test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload README.md
Browse files
README.md
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thumbnail: "Keywords to Sentences"
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tags:
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- keytotext
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- k2t
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- Keywords to Sentences
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---
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language: "en"
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thumbnail: "Keywords to Sentences"
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tags:
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- keytotext
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- k2t
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- Keywords to Sentences
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model-index:
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- name: k2t-test
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Idea is to build a model which will take keywords as inputs and generate sentences as outputs.
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Potential use case can include:
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- Marketing
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- Search Engine Optimization
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- Topic generation etc.
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- Fine tuning of topic modeling models
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