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--- |
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tags: |
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- autotrain |
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- text-generation-inference |
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- text-generation |
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- peft |
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library_name: transformers |
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widget: |
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- messages: |
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- role: user |
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content: What is your favorite condiment? |
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license: other |
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--- |
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# Model Trained Using AutoTrain |
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This model was trained using AutoTrain. For more information, please visit [AutoTrain](https://hf.co/docs/autotrain). |
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Dataset used: codeparrot/xlcost-text-to-code |
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github: https://github.com/manishzed/LLM-Fine-tune |
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# Usage |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_path = "kr-manish/Mistral-7B-autotrain-text-python-vf1" |
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tokenizer = AutoTokenizer.from_pretrained(model_path) |
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model = AutoModelForCausalLM.from_pretrained(model_path) |
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#input_text = "Maximum Prefix Sum possible by merging two given arrays | Python3 implementation of the above approach ; Stores the maximum prefix sum of the array A [ ] ; Traverse the array A [ ] ; Stores the maximum prefix sum of the array B [ ] ; Traverse the array B [ ] ;" |
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input_text ="Program to convert Centimeters to Pixels | Function to convert centimeters to pixels ; Driver Code" |
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# Tokenize input text |
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input_ids = tokenizer.encode(input_text, return_tensors="pt") |
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# Generate output text |
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output = model.generate(input_ids, max_length=1024, num_return_sequences=1, do_sample=True) |
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# Decode and print output |
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generated_text = tokenizer.decode(output[0], skip_special_tokens=True) |
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print(generated_text) |
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#Program to convert Centimeters to Pixels | Function to convert centimeters to pixels ; Driver Code [/INST] def cmToPixels ( cm ) : NEW_LINE INDENT return ( ( cm * 100 ) / 17 ) NEW_LINE DEDENT cm = 105.25 NEW_LINE print ( round ( cmToPixels ( cm ) , 3 ) ) NEW_LINE |
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``` |