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--- |
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license: llama3.2 |
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tags: |
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- unsloth |
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- text-generation |
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datasets: |
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- marmikpandya/mental-health |
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- Amod/mental_health_counseling_conversations |
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- AdithyaSK/CompanionLLama_instruction_30k |
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base_model: |
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- unsloth/Llama-3.2-3B-Instruct |
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library_name: transformers |
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--- |
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# Model Card for Model ID |
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<!-- Provide a quick summary of what the model is/does. --> |
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This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1). |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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This model has been fine-tuned for use in a chatbot aimed at mental well-being support. It is designed to offer empathetic, supportive responses to users' mental health inquiries. A combined dataset was created by merging three relevant datasets for training to enhance the model’s ability to understand and respond appropriately in counseling scenarios. |
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- **Developed by:** Ayesha Noor |
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- **Model type:** Language model for conversational AI |
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- **Language(s) (NLP):** English |
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- **Finetuned from model:** unsloth/Llama-3.2-3B-Instruct |
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### Model Sources |
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<!-- Provide the basic links for the model. --> |
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- **Repository:** https://huggingface.co/ayeshaNoor1 |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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### Direct Use |
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. --> |
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Intended for mental health chatbot applications, particularly for providing initial support, resources, and empathetic responses in mental well-being conversations. |
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### Downstream Use |
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app --> |
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May be used as part of broader mental health support applications, integrated into platforms aimed at user well-being. |
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### Out-of-Scope Use |
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. --> |
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Not recommended for critical mental health assessments, as it is not a replacement for professional help. Avoid using for high-stakes decision-making without appropriate oversight. |
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### Recommendations |
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
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Users should be aware of the limitations in handling diverse mental health needs and sensitive conversations. Professional oversight is advised when using in serious or emergency mental health contexts. |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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from transformers import AutoTokenizer, AutoModelForCausalLM |
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tokenizer = AutoTokenizer.from_pretrained("ayeshaNoor1/Llama_finetunedModel") |
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model = AutoModelForCausalLM.from_pretrained("ayeshaNoor1/Llama_finetunedModel") |
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inputs = tokenizer("Your text here", return_tensors="pt") |
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outputs = model.generate(**inputs) |
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## Training Details |
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### Training Data |
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<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. --> |
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A single dataset was created by merging: |
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- **First Dataset:** - marmikpandya/mental-health |
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- **Second Dataset:** - Amod/mental_health_counseling_conversations |
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- **Third Dataset:** - AdithyaSK/CompanionLLama_instruction_30k |
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### Training Procedure |
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<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. --> |
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#### Preprocessing [optional] |
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Data was preprocessed to ensure consistency in format, relevance to mental health support, and removal of any sensitive or personal identifiers. |
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#### Summary |
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The model demonstrated proficiency in providing supportive responses in well-being conversations. |
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## Technical Specifications [optional] |
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### Compute Infrastructure |
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#### Software |
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- **Libraries:** transformers, datasets, torch, pandas, trl, unsloth |
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- **Framework:** PyTorch |
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