Question Answering
Transformers
Safetensors
English
llama
text-generation
rag
text-generation-inference
Instructions to use DISLab/Ext2Gen-8B-R2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DISLab/Ext2Gen-8B-R2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="DISLab/Ext2Gen-8B-R2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DISLab/Ext2Gen-8B-R2") model = AutoModelForCausalLM.from_pretrained("DISLab/Ext2Gen-8B-R2") - Notebooks
- Google Colab
- Kaggle
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Are you looking for a more robust and reliable generation model for RAG system?
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Here is a Ext2Gen-8B-R2 model that effectively mitigates hallucinations caused by retrieval noise and information overload.
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<b style="font-size: 40px;">Ext2Gen-8B-R2</b>
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Note: We are still working on this.
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Are you looking for a more robust and reliable generation model for RAG system?
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Here is a Ext2Gen-8B-R2 model that effectively mitigates hallucinations caused by retrieval noise and information overload.
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