118 lines
4.3 KiB
Markdown
118 lines
4.3 KiB
Markdown
---
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base_model: unsloth/qwen2-0.5b-bnb-4bit
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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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- qwen2
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- trl
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- sft
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---
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1 - # alpaca_prompt = Copied from above
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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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# "Continue the fibonnaci sequence.", # instruction
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# "1, 1, 2, 3, 5, 8", # 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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outputs = model.generate(**inputs, max_new_tokens = 128, use_cache = True)
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tokenizer.batch_decode(outputs)
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['Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.\n\n### Input:\nContinue the fibonnaci sequence.\n\n### Output:\n1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765, 10946, 17711, 28657, 46368, 75025, 121393, 196728, 318101']
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2 - # alpaca_prompt = Copied from above
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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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# "What is fibonacci sequence?", # instruction
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"", # 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 = 256)
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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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### Input:
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What is fibonacci sequence?
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### Output:
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The Fibonacci sequence is a series of numbers in which each number is the sum of the two preceding ones, usually starting with 0 and 1. The sequence goes like this: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597, 2584, 4181, 6765, 10946, 17711, 28657, 46368, 75025, 121393, 196728, 328101, 544829, 973530, 1518361, 2492891, 4011452, 6504307, 9518768, 15023075
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3 - if False:
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from unsloth import FastLanguageModel
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model, tokenizer = FastLanguageModel.from_pretrained(
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model_name = "lora_model", # YOUR MODEL YOU USED FOR TRAINING
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max_seq_length = max_seq_length,
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dtype = dtype,
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load_in_4bit = load_in_4bit,
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)
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FastLanguageModel.for_inference(model) # Enable native 2x faster inference
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# alpaca_prompt = You MUST copy from above!
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inputs = tokenizer(
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[
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alpaca_prompt.format(
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# "Crie uma IA. Ela será treinada para conversar por chat e escrever códigos em python conforme solicitada, após ser treinada para essas tarefas.", # instruction
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"", # 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 = 4096)
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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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### Input:
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Crie uma IA. Ela será treinada para conversar por chat e escrever codigos em python conforme solicitada, após ser treinada para essas tarefas.
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### Output:
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Here is a simple Python program that uses the OpenAI's ChatGPT API to simulate a chatbot:
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```python
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import openai
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from openai import ChatGPT
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# Initialize the ChatGPT API
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openai.api_key = "YOUR_API_KEY"
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# Create a ChatGPT model
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model = ChatGPT(model_name="gpt-3.5-turbo")
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# Create a prompt
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prompt = "Write a python program that takes a number as input and prints out the square of that number."
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# Send the prompt to the ChatGPT model
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response = model.create(input=prompt)
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# Print the response
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print(response)
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```
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This program will output a Python program that takes a number as input and prints out the square of that number.<|endoftext|>
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# Uploaded model
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- **Developed by:** Ramikan-BR
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- **License:** apache-2.0
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- **Finetuned from model :** unsloth/qwen2-0.5b-bnb-4bit
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This qwen2 model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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