| --- |
| base_model: unsloth/deepseek-r1-distill-qwen-7b-unsloth-bnb-4bit |
| tags: |
| - text-generation-inference |
| - transformers |
| - unsloth |
| - qwen2 |
| - trl |
| license: apache-2.0 |
| language: |
| - en |
| --- |
| |
| # MaWared HR Reasoning Model |
|
|
| ## Model Details |
|
|
| - **Base Model:** [unsloth/deepseek-r1-distill-qwen-7b-unsloth-bnb-4bit](https://huggingface.co/unsloth/deepseek-r1-distill-qwen-7b-unsloth-bnb-4bit) |
| - **Finetuned by:** Daemontatox |
| - **License:** Apache-2.0 |
| - **Language:** English |
| - **Tags:** text-generation-inference, transformers, unsloth, qwen2, trl |
|
|
| ## Overview |
|
|
| This model is a finetuned version of the `deepseek-r1-distill-qwen-7b` model, optimized for MaWared HR reasoning. It was trained using [Unsloth](https://github.com/unslothai/unsloth) and Hugging Face's TRL library, enabling 2x faster training performance. |
|
|
| ## Features |
|
|
| - **HR Query Reasoning:** Provides logical and well-structured responses to complex HR-related inquiries. |
| - **Decision Support:** Assists HR professionals in making informed decisions based on policies and regulations. |
| - **Enhanced Performance:** Optimized for deep reasoning and contextual understanding in HR-related scenarios. |
|
|
| ## Installation |
|
|
| To use this model, install the required dependencies: |
|
|
| ```bash |
| pip install torch transformers accelerate unsloth |
| |
| ``` |
|
|
| ## Usage |
| You can load and use the model with the following Python snippet: |
| ``` |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| import torch |
| |
| model_name = "Daemontatox/mawared-hr-reasoning" |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
| model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto") |
| |
| input_text = "How should I handle a conflict between employees?" |
| inputs = tokenizer(input_text, return_tensors="pt").to("cuda") |
| output = model.generate(**inputs, max_length=100) |
| response = tokenizer.decode(output[0], skip_special_tokens=True) |
| print(response) |
| ``` |
|
|
|
|
| ## Acknowledgments |
| This model was developed using Unsloth and Hugging Face's TRL library. Special thanks to the open-source community for their contributions. |
|
|
| License |
| This model is licensed under the Apache-2.0 license. |
|
|
| vbnet |
| ``` |
| |
| Let me know if you need any modifications! 🚀 |
| ``` |
|
|
|
|
