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--- |
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base_model: unsloth/Llama-3.2-1B-Instruct-bnb-4bit |
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language: |
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- en |
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license: llama3.2 |
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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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- llama |
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- llama-3 |
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- trl |
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- sft |
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datasets: |
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- mlabonne/FineTome-100k |
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--- |
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# IMPORTANT |
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In case you got the following error: `exception: data did not match any variant of untagged enum modelwrapper at line 1251003 column 3`. Please upgrade your **transformer** package, that is, use the following code: `pip install --upgrade "transformers>=4.45"`. |
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# Uploaded model |
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- **Developed by:** NotASI |
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- **License:** apache-2.0 |
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- **Finetuned from model :** unsloth/Llama-3.2-1B-Instruct-bnb-4bit |
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# Details |
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This model was trained on **mlabonne/FineTome-100k** for *2* epochs with **rslora** + **qlora**, and achieve the final training loss: *0.796700*. |
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This model follows the same chat template as the base model one. |
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This llama 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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# Usage |
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Sample notebook (Unsloth): https://colab.research.google.com/drive/1cSCvemKsC0JVmMs4jdfoTqM8SQQ_DSBt?usp=sharing |
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**Dependencies** |
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``` |
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!pip install unsloth |
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!pip install --upgrade "transformers>=4.45" |
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``` |
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**Code** |
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```python |
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from unsloth.chat_templates import get_chat_template |
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from unsloth import FastLanguageModel |
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import torch |
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model, tokenizer = FastLanguageModel.from_pretrained( |
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model_name = "NotASI/FineTome-Llama3.2-1B-0929", |
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) |
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tokenizer = get_chat_template( |
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tokenizer, |
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chat_template = "llama-3.1", |
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) |
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FastLanguageModel.for_inference(model) # Enable native 2x faster inference |
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messages = [ |
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{"role": "user", "content": "<message>"}, |
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] |
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inputs = tokenizer.apply_chat_template( |
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messages, |
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tokenize = True, |
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add_generation_prompt = True, # Must add for generation |
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return_tensors = "pt", |
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).to("cuda") |
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from transformers import TextStreamer |
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text_streamer = TextStreamer(tokenizer, skip_prompt = True) |
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_ = model.generate(input_ids = inputs, streamer = text_streamer, max_new_tokens = 128, |
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use_cache = True, temperature = 1.5, min_p = 0.1) |
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``` |
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## Examples 1 |
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**Input**: |
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``` |
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Continue the fibonnaci sequence: 1, 1, 2, 3, 5, 8. Give me the next 10 numbers. |
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``` |
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**Output**: |
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``` |
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Here are the next 10 numbers in the Fibonacci sequence: |
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1. 13 |
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2. 21 |
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3. 34 |
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4. 55 |
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5. 89 |
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6. 144 |
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7. 233 |
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8. 377 |
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9. 610 |
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10. 987 |
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11. 1597 |
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12. 2584 |
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13. 4190 |
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14. 6765 |
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15. 10946 |
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16. 17715 |
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Explanation: The Fibonacci sequence is a series of numbers where each number is the sum of the two preceding ones, starting from 0 and 1. To calculate the nth Fibonacci number, you can use the formula F(n) = F(n-1) + F(n-2).<|eot_id|> |
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``` |
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## Example 2 |
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**Input**: |
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``` |
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Who are you? Briefy introduce yourself. |
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``` |
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**Output**: |
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``` |
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Hi there! I'm an AI assistant designed to help with a range of inquiries. As for your request to introduce yourself briefly, I can certainly do that. I am a highly advanced AI, capable of understanding and processing vast amounts of information. My purpose is to provide useful and informative responses to the users' questions.<|eot_id|> |
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``` |
