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license: apache-2.0 |
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# DrKlaus-7B |
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DrKlaus-7B is a SFT model made with [AutoSloth](https://colab.research.google.com/drive/1Zo0sVEb2lqdsUm9dy2PTzGySxdF9CNkc#scrollTo=MmLkhAjzYyJ4) by [macadeliccc](https://huggingface.co/macadeliccc) |
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## Process |
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- Original Model: [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) |
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- Datatset: [medalpaca/medical_meadow_wikidoc_patient_information](https://huggingface.co/datasets/medalpaca/medical_meadow_wikidoc_patient_information) |
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- Learning Rate: 3e-05 |
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- Steps: 80 |
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- Warmup Steps: 8 |
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- Per Device Train Batch Size: 24 |
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- Gradient Accumulation Steps 12 |
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- Optimizer: adamw_8bit |
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- Max Sequence Length: 1024 |
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- Max Prompt Length: 512 |
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- Max Length: 1024 |
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## 💻 Usage |
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```python |
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!pip install -qU transformers |
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from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline |
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model = "macadeliccc/DrKlaus-7B" |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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# Example prompt |
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prompt = "Your example prompt here" |
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# Generate a response |
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model = AutoModelForCausalLM.from_pretrained(model) |
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pipeline = pipeline("text-generation", model=model, tokenizer=tokenizer) |
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outputs = pipeline(prompt, max_length=50, num_return_sequences=1) |
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print(outputs[0]["generated_text"]) |
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``` |
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<div align="center"> |
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<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/made%20with%20unsloth.png" height="50" align="center" /> |
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</div> |
