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README.md

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----
-library_name: transformers
-tags: []
----
-
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
+# CPU Compatible Mental Health Chatbot Model
 
-## Training Details
+This repository contains a fine-tuned LLaMA-based model designed for mental health counseling conversations. The model provides meaningful and empathetic responses to mental health-related queries. It is compatible with CPUs and systems with low RAM, making it accessible for a wide range of users.
 
-### Training Data
-
-<!-- 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. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
+---
 
-[More Information Needed]
+## Features
 
-#### Summary
+- **Fine-tuned on Mental Health Counseling Conversations**: The model is trained using a dataset specifically curated for mental health support.
+- **Low Resource Requirements**: Fully executable on systems with 15 GB RAM and CPU, no GPU required.
+- **Pretrained on Meta's LLaMA 3.2 1B Model**: Builds on the strengths of the LLaMA architecture for high-quality responses.
+- **Supports LoRA (Low-Rank Adaptation)**: Enables efficient fine-tuning with low computational overhead.
 
+---
 
+## Model Details
 
-## Model Examination [optional]
+- **Base Model**: [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct)
+- **Dataset**: [Amod/Mental Health Counseling Conversations](https://huggingface.co/datasets/Amod/mental_health_counseling_conversations)
+- **Fine-Tuning Framework**: Hugging Face Transformers
 
-<!-- Relevant interpretability work for the model goes here -->
+---
 
-[More Information Needed]
+## Installation
 
-## Environmental Impact
+1. Clone the repository:
+    ```bash
+    git clone https://huggingface.co/<your_hf_username>/mental-health-chatbot-model
+    cd mental-health-chatbot-model
+    ```
 
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+2. Install the required packages:
+    ```bash
+    pip install torch transformers datasets huggingface-hub
+    ```
 
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+---
 
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
+## Usage
 
-## Technical Specifications [optional]
+### Load the Model
 
-### Model Architecture and Objective
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
 
-[More Information Needed]
+# Load model and tokenizer
+model_name = "<your_hf_username>/mental-health-chatbot-model"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
 
-### Compute Infrastructure
+# Generate a response
+input_text = "I feel anxious and don't know what to do."
+inputs = tokenizer(input_text, return_tensors="pt")
+response = model.generate(**inputs, max_length=256, pad_token_id=tokenizer.eos_token_id)
+print(tokenizer.decode(response[0], skip_special_tokens=True))
+```
 
-[More Information Needed]
+### Compatibility
 
-#### Hardware
+This model can be run on:
+- CPU-only systems
+- Machines with as little as 15 GB RAM
 
-[More Information Needed]
+---
 
-#### Software
+## Fine-Tuning Instructions
 
-[More Information Needed]
+To further fine-tune the model on your dataset:
 
-## Citation [optional]
+1. Prepare your dataset in Hugging Face Dataset format.
+2. Use the following script:
 
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+```python
+from transformers import Trainer, TrainingArguments
 
-**BibTeX:**
+training_args = TrainingArguments(
+    output_dir="./fine_tuned_model",
+    per_device_train_batch_size=4,
+    num_train_epochs=3,
+    evaluation_strategy="epoch",
+    save_steps=500,
+    logging_dir="./logs",
+    learning_rate=5e-5,
+)
 
-[More Information Needed]
+trainer = Trainer(
+    model=model,
+    args=training_args,
+    train_dataset=train_dataset,
+    eval_dataset=validation_dataset,
+)
 
-**APA:**
+trainer.train()
+```
 
-[More Information Needed]
+---
 
-## Glossary [optional]
+## Model Performance
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+- **Training Epochs**: 3
+- **Batch Size**: 4
+- **Learning Rate**: 5e-5
+- **Evaluation Strategy**: Epoch-wise
 
-[More Information Needed]
+---
 
-## More Information [optional]
+## License
 
-[More Information Needed]
+This project is licensed under the [Apache 2.0 License](LICENSE).
 
-## Model Card Authors [optional]
+---
 
-[More Information Needed]
+## Acknowledgments
 
-## Model Card Contact
+- [Meta](https://huggingface.co/meta-llama) for the LLaMA model
+- [Hugging Face](https://huggingface.co/) for their open-source tools and datasets
+- The creators of the Mental Health Counseling Conversations dataset
 
-[More Information Needed]