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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 818a28d96a15297acddbd7df1ddcc7f4760c77cbecc24ba91bdf44485e8b0be0
- Size of remote file:
- 6.71 GB
- SHA256:
- ffe2fccc90b3b9c8bb376f4296694a88321541319d12b6c39ee320e93d8a01ba
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