Add library_name and link to Github repo
#3
by
nielsr
HF Staff
- opened
README.md
CHANGED
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@@ -1,5 +1,6 @@
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---
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-
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datasets:
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- HiTZ/GuideX_pre-training_data
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- ACE05
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@@ -12,10 +13,9 @@ datasets:
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- wnut_17
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language:
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- en
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metrics:
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- f1
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base_model:
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- meta-llama/Llama-3.1-8B
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tags:
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- code
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- text-generation-inference
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- Event Extraction
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- Relation Extraction
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- LLaMA
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---
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<p align=
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# Model Card for GuideX-8B
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<p align="center">
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This model achieves state-of-the-art performance on zero-shot Named Entity Recognition (NER) by first training on `GuideX`, a large-scale synthetic dataset with executable guidelines, and then fine-tuning on a collection of gold-standard IE datasets.
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- **Homepage:** [https://neilus03.github.io/guidex.com/](https://neilus03.github.io/guidex.com/)
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- **Paper:** [GuideX: Guided Synthetic Data Generation for Zero-Shot Information Extraction](https://
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- **Code & Data:** The code and data for reproducing the GuideX methodology are available on the project homepage.
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## Model Description
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- **Model type:** Decoder-only Transformer (Text Generation)
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- **Language(s):** English
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- **License:** Llama 2 Community License
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- **Finetuned from model:** `meta-llama/Llama-3.1-8B`
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-
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---
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base_model:
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- meta-llama/Llama-3.1-8B
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datasets:
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- HiTZ/GuideX_pre-training_data
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- ACE05
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- wnut_17
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language:
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- en
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license: apache-2.0
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metrics:
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- f1
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tags:
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- code
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- text-generation-inference
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- Event Extraction
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- Relation Extraction
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- LLaMA
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pipeline_tag: text-generation
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library_name: transformers
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---
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<p align=
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# Model Card for GuideX-8B
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<p align="center">
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This model achieves state-of-the-art performance on zero-shot Named Entity Recognition (NER) by first training on `GuideX`, a large-scale synthetic dataset with executable guidelines, and then fine-tuning on a collection of gold-standard IE datasets.
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- **Homepage:** [https://neilus03.github.io/guidex.com/](https://neilus03.github.io/guidex.com/)
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- **Paper:** [GuideX: Guided Synthetic Data Generation for Zero-Shot Information Extraction](https://huggingface.co/papers/2506.00649)
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- **Code & Data:** The code and data for reproducing the GuideX methodology are available on the project homepage and on [Github](https://github.com/HiTZ/GUIDEX).
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## Model Description
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- **Model type:** Decoder-only Transformer (Text Generation)
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- **Language(s):** English
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- **License:** Llama 2 Community License
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- **Finetuned from model:** `meta-llama/Llama-3.1-8B`
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