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README.md
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license:
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model-index:
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- name: camoscio-7b-llama
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results: []
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should probably proofread and complete it, then remove this comment. -->
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 0.0003
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- train_batch_size: 4
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 32
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- total_train_batch_size: 128
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 100
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- num_epochs: 3
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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- Transformers 4.27.0.dev0
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- Pytorch 2.0.0+cu118
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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license: openrail
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language:
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- it
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# Camoscio: An Italian instruction-tuned LLaMA
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## Usage
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Check the Github repo with code: https://github.com/teelinsan/camoscio
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```python
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from peft import PeftModel
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from transformers import LLaMATokenizer, LLaMAForCausalLM, GenerationConfig
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tokenizer = LLaMATokenizer.from_pretrained("decapoda-research/llama-7b-hf")
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model = LLaMAForCausalLM.from_pretrained(
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"decapoda-research/llama-7b-hf",
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load_in_8bit=True,
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device_map="auto",
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)
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model = PeftModel.from_pretrained(model, "teelinsan/camoscio-7b-llama")
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```
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Generation Example: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/teelinsan/camoscio/blob/master/notebooks/camoscio-lora.ipynb)
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