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--- |
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language: |
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- en |
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license: apache-2.0 |
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tags: |
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- text-generation-inference |
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- transformers |
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- unsloth |
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- gemma |
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- trl |
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base_model: unsloth/gemma-7b-bnb-4bit |
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--- |
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# gemma-alpacha |
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> yahma/alpaca-cleaned finetuned with gemma-7b-bnb-4bit |
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# Usage |
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```sh |
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pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git" |
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``` |
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```py |
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from unsloth import FastLanguageModel |
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model, tokenizer = FastLanguageModel.from_pretrained("gnumanth/gemma-unsloth-alpaca") |
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``` |
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```py |
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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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### Instruction: |
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{} |
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### Input: |
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{} |
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### Response: |
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{}""" |
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``` |
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```py |
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FastLanguageModel.for_inference(model) # Enable native 2x faster inference |
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inputs = tokenizer( |
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[ |
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alpaca_prompt.format( |
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"Give me a python code for quicksort", # instruction |
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"1,-1,0,8,9,-2,2", # input |
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"", # output - leave this blank for generation! |
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) |
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], return_tensors = "pt").to("cuda") |
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from transformers import TextStreamer |
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text_streamer = TextStreamer(tokenizer) |
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_ = model.generate(**inputs, streamer = text_streamer, max_new_tokens = 128) |
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``` |
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```sh |
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<bos>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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### Instruction: |
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Give me a python code for quicksort |
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### Input: |
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1,-1,0,8,9,-2,2 |
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### Response: |
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def quicksort(arr): |
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if len(arr) <= 1: |
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return arr |
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pivot = arr[0] |
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left = [i for i in arr[1:] if i < pivot] |
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right = [i for i in arr[1:] if i >= pivot] |
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return quicksort(left) + [pivot] + quicksort(right)<eos> |
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``` |
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[Hemanth HMM](https://h3amnth.com) | (Built with [unsloth](https://unsloth.ai)) |
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