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--- |
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library_name: transformers |
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tags: |
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- trl |
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- sft |
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license: mit |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated. |
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- **Developed by:** Sefika |
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- **Language(s) (NLP):** EN |
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- **License:** MIT |
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- **Finetuned from model [optional]:** mistralai/Mistral-7B-Instruct-v0.2 |
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### Model Sources [optional] |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** [More Information Needed] |
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- **Paper [optional]:** [More Information Needed] |
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- **Demo [optional]:** [More Information Needed] |
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### Direct Use |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline |
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tokenizer = "mistralai/Mistral-7B-Instruct-v0.2" |
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model_id = "Sefika/mistral_fewrel_10_1" |
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tokenizer = AutoTokenizer.from_pretrained(model_id, use_auth_token=True) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_id, |
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device_map="auto", |
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load_in_4bit=True, # Requires bitsandbytes |
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torch_dtype="auto" |
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) |
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``` |
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#### Testing Data |
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FewRel |
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**BibTeX:** |
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The paper "Large Language Models for Continual Relation Extraction" is submitted to Springer Machine Learning journal |
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## Model Card Contact |
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sefika efeoglu |
