Question Answering
Transformers
PyTorch
Safetensors
English
distilbert
conversational-ai
nlp
context-aware
Eval Results (legacy)
Instructions to use harpertoken/harpertokenConvAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use harpertoken/harpertokenConvAI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="harpertoken/harpertokenConvAI")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("harpertoken/harpertokenConvAI") model = AutoModelForQuestionAnswering.from_pretrained("harpertoken/harpertokenConvAI") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f0923a7b2819c86743d10fcc8af15651835cf29456772326292e3c70ca96ba15
- Size of remote file:
- 265 MB
- SHA256:
- 20e153a0baf9bf96c82063ef9232e6293d5d47f73b91c07d35535752b8b556cb
路
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