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+ ---
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+ library_name: peft
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+ base_model: unsloth/tinyllama-bnb-4bit
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+ license: mit
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+ datasets:
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+ - yahma/alpaca-cleaned
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+ language:
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+ - en
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+ pipeline_tag: text-generation
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+ tags:
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+ - Instruct
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+ - TinyLlama
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+ ---
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+
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+ # Steps to try the model:
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+
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+ ### prompt Template
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+ ```python
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+ alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
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+
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+ ### Instruction:
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+ {}
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+
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+ ### Input:
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+ {}
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+
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+ ### Response:
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+ {}"""
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+ ```
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+ ### load the model
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+
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+ ```python
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+ from peft import PeftModel, PeftConfig
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+ from transformers import AutoModelForCausalLM ,AutoTokenizer
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+
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+ config = PeftConfig.from_pretrained("damerajee/Tinyllama-sft-small")
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+ model = AutoModelForCausalLM.from_pretrained("unsloth/tinyllama")
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+ tokenizer=AutoTokenizer.from_pretrained("damerajee/Tinyllama-sft-small")
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+ model = PeftModel.from_pretrained(model, "damerajee/Tinyllama-sft-small")l")
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+
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+ ```
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+ ### Inference
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+
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+ ```python
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+ inputs = tokenizer(
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+ [
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+ alpaca_prompt.format(
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+ "i want to learn machine learning help me",
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+ "", # input
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+ "", # output
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+ )
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+ ]*1, return_tensors = "pt").to("cuda")
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+
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+ outputs = model.generate(**inputs, max_new_tokens = 312, use_cache = True)
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+ tokenizer.batch_decode(outputs)
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+ ```
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+
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+ # Model Information
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+ The base model [unsloth/tinyllama-bnb-4bit](https://huggingface.co/unsloth/tinyllama-bnb-4bit)was Instruct finetuned using [Unsloth](https://github.com/unslothai/unsloth)
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+
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+ # Training Details
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+
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+ The model was trained for 1 epoch on a free goggle colab which took about 1 hour and 30 mins approximately