Instructions to use pyteach237/multilabel_lora_distilbert_runews_classifier_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use pyteach237/multilabel_lora_distilbert_runews_classifier_tuned with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("distilbert-base-multilingual-cased") model = PeftModel.from_pretrained(base_model, "pyteach237/multilabel_lora_distilbert_runews_classifier_tuned") - Notebooks
- Google Colab
- Kaggle
updated card
Browse files
README.md
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model-index:
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- name: multilabel_lora_distilbert_runews_classifier_tuned
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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#
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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model-index:
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- name: multilabel_lora_distilbert_runews_classifier_tuned
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results: []
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datasets:
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- pyteach237/news_classify
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language:
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- ru
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- fr
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- en
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# # Model Card: DistilBERT with LoRA for Text Classification
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## Model Details
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**Model Name:** DistilBERT with LoRA for Text Classification
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**Model Type:** Transformer-based Language Model
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**Base Model:** `distilbert-base-multilingual-cased`
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**Fine-tuning Framework:** LoRA (Low-Rank Adaptation of Large Language Models)
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**Trained By:** ABODO ELOUNDOU Brice Donald
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**License:** Apache 2.0
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This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
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It achieves the following results on the evaluation set:
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