Instructions to use DarioNaviar/long-writer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DarioNaviar/long-writer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DarioNaviar/long-writer", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -3,13 +3,13 @@ license: other
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license_name: glm-4
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license_link: https://huggingface.co/THUDM/glm-4-9b-chat/blob/main/LICENSE
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language:
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- en
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tags:
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inference: false
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---
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# GLM-4-9B-Chat
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archivePrefix={arXiv},
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primaryClass={id='cs.CL' full_name='Computation and Language' is_active=True alt_name='cmp-lg' in_archive='cs' is_general=False description='Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.'}
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}
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```
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license_name: glm-4
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license_link: https://huggingface.co/THUDM/glm-4-9b-chat/blob/main/LICENSE
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language:
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- en
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tags:
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- glm
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- chatglm
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- thudm
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inference: false
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library_name: transformers
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---
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# GLM-4-9B-Chat
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archivePrefix={arXiv},
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primaryClass={id='cs.CL' full_name='Computation and Language' is_active=True alt_name='cmp-lg' in_archive='cs' is_general=False description='Covers natural language processing. Roughly includes material in ACM Subject Class I.2.7. Note that work on artificial languages (programming languages, logics, formal systems) that does not explicitly address natural-language issues broadly construed (natural-language processing, computational linguistics, speech, text retrieval, etc.) is not appropriate for this area.'}
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}
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```
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