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--- |
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base_model: unsloth/mistral-7b-instruct-v0.2-bnb-4bit |
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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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- mistral |
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- trl |
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license: apache-2.0 |
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language: |
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- en |
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--- |
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Download the model |
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```python |
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# This is to set the path to save the model |
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from pathlib import Path |
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models_path = Path.home().joinpath('Question_Generation_model', 'UTeMGPT') |
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models_path.mkdir(parents=True, exist_ok=True) |
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# Download the model |
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from huggingface_hub import snapshot_download |
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my_model = snapshot_download(repo_id="KLimaLima/finetuned-Question-Generation-mistral-7b-instruct", local_dir=models_path) |
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``` |
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To load the model that have been downloaded |
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```python |
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max_seq_length = 2048 # Choose any! We auto support RoPE Scaling internally! |
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dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+ |
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load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False. |
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from unsloth import FastLanguageModel |
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model, tokenizer = FastLanguageModel.from_pretrained( |
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model_name = my_model, |
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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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``` |
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This model uses alpaca prompt format such as below |
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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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### 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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instruction = 'Write an inquisitive question about a specific text span in a given sentence such that the answer is not in the text.' |
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sentence = "I want to bake a cake during my free time. I need to know the ingredients that need to be use." |
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inputs = tokenizer( |
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[ |
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alpaca_prompt.format( |
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instruction, |
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sentence, |
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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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``` |
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To generate output |
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```python |
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outputs = model.generate(**inputs, max_new_tokens = 64, use_cache = True) |
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tokenizer.batch_decode(outputs) |
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``` |
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# Uploaded model |
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- **Developed by:** KLimaLima |
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- **License:** apache-2.0 |
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- **Finetuned from model :** unsloth/mistral-7b-instruct-v0.2-bnb-4bit |
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This mistral 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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