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README.md
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@@ -8,7 +8,6 @@ pipeline_tag: text-generation
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---
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## Training procedure
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-
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: False
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- load_in_4bit: True
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- bnb_4bit_compute_dtype: bfloat16
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### Framework versions
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-
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---
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## Training procedure
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The following `bitsandbytes` quantization config was used during training:
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- load_in_8bit: False
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- load_in_4bit: True
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- bnb_4bit_compute_dtype: bfloat16
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### Framework versions
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- PEFT 0.4.0
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# How to use:
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```
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!pip install transformers peft accelerate bitsandbytes trl safetensors
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from huggingface_hub import notebook_login
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notebook_login()
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import torch
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from peft import AutoPeftModelForCausalLM, get_peft_config, PeftModel, PeftConfig, get_peft_model, LoraConfig, TaskType
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from transformers import AutoTokenizer
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peft_model_id = "akdeniz27/llama-2-7b-hf-qlora-dolly15k-turkish"
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config = PeftConfig.from_pretrained(peft_model_id)
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# load base LLM model and tokenizer
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model = AutoPeftModelForCausalLM.from_pretrained(
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peft_model_id,
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low_cpu_mem_usage=True,
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torch_dtype=torch.float16,
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load_in_4bit=True,
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)
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tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
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prompt = "..."
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input_ids = tokenizer(prompt, return_tensors="pt", truncation=True).input_ids.cuda()
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outputs = model.generate(input_ids=input_ids, max_new_tokens=100, do_sample=True, top_p=0.9,temperature=0.9)
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```
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