Text Classification
Transformers
Safetensors
PyTorch
English
Spanish
t5
text2text-generation
cognitive-patterns
evaluation
benchmark
axolotl
NHE
imprint-theory
human-cognition
fine-tuned
Instructions to use Not-Humanity-Exam/Imprint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Not-Humanity-Exam/Imprint with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Not-Humanity-Exam/Imprint")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Not-Humanity-Exam/Imprint") model = AutoModelForSeq2SeqLM.from_pretrained("Not-Humanity-Exam/Imprint") - Notebooks
- Google Colab
- Kaggle
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- imprint-theory
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- human-cognition
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pipeline_tag:
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model-index:
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- name: Imprint-v1
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results: []
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- imprint-theory
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- human-cognition
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- fine-tuned
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pipeline_tag: text-classification
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model-index:
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- name: Imprint-v1
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results: []
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