Instructions to use uzabase/LLM2Vec-Llama-2-7b-hf-mntp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use uzabase/LLM2Vec-Llama-2-7b-hf-mntp with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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- **Repository:** https://github.com/McGill-NLP/llm2vec
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- **Paper:** https://arxiv.org/abs/2404.05961
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#
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- Please see [original LLM2Vec repo](https://huggingface.co/McGill-NLP/LLM2Vec-Llama-2-7b-chat-hf-mntp#usage)
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##
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- [wikitext](https://huggingface.co/datasets/Salesforce/wikitext)
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##
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- batch_size: 64,
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- gradient_accumulation_steps: 1
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- max_seq_length": 512,
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- bf16: true
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- gradient_checkpointing: true
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- deepspeed_config:
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- gradient_accumulation_steps: 1
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- gradient_clipping: 1.0
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- quse_cpu: false
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##
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- Python: 3.12.3
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- PEFT 0.11.1
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- **Repository:** https://github.com/McGill-NLP/llm2vec
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- **Paper:** https://arxiv.org/abs/2404.05961
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# Usage
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- Please see [original LLM2Vec repo](https://huggingface.co/McGill-NLP/LLM2Vec-Llama-2-7b-chat-hf-mntp#usage)
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# Training Details
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## Training Data
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- [wikitext](https://huggingface.co/datasets/Salesforce/wikitext)
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## Training Hyperparameter
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- batch_size: 64,
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- gradient_accumulation_steps: 1
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- max_seq_length": 512,
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- bf16: true
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- gradient_checkpointing: true
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## Accelerator Settings
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- deepspeed_config:
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- gradient_accumulation_steps: 1
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- gradient_clipping: 1.0
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- quse_cpu: false
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## Framework versions
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- Python: 3.12.3
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- PEFT 0.11.1
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