suvadeep29
/

Luna-4B-thinking

@@ -1,200 +1,84 @@
 ---
-library_name: transformers
 tags:
-- unsloth
 ---
-# 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]
-## Training Details
-### 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]
-#### Summary
-## Model Examination [optional]
-<!-- Relevant interpretability work for the model goes here -->
-[More Information Needed]
-## Environmental Impact
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-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]
-## Technical Specifications [optional]
-### Model Architecture and Objective
-[More Information Needed]
-### Compute Infrastructure
-[More Information Needed]
-#### Hardware
-[More Information Needed]
-#### Software
-[More Information Needed]
-## Citation [optional]
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-**BibTeX:**
-[More Information Needed]
-**APA:**
-[More Information Needed]
-## Glossary [optional]
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-[More Information Needed]
-## More Information [optional]
-[More Information Needed]
-## Model Card Authors [optional]
-[More Information Needed]
-## Model Card Contact
-[More Information Needed]

 ---
+language:
+- en
+license: apache-2.0
 tags:
+- mental-health
+- psychiatry
+- psychology
+- qwen3
+- medical
+- therapy
+- gguf
+base_model: Qwen/Qwen3-4B-Thinking-2507
+library_name: transformers
+pipeline_tag: text-generation
 ---
+# Luna 1.0 - Psychiatric AI Companion
+## Model Description
+Luna is a 4B parameter psychiatric AI trained through 8-stage curriculum learning on Qwen3-4B-Thinking-2507. Created by Dr. Suvadeep.
+**Training Stages:**
+- Stage 1-2: Psychiatric knowledge (DSM-5, medications, CBT, counseling)
+- Stage 3-7: Empathy & conversation skills (30,000+ dialogues)
+- Stage 8: Identity & anti-refusal training
+**Capabilities:**
+- DSM-5/ICD-11 diagnoses
+- Medication recommendations with dosages
+- CBT/DBT/ACT psychotherapy
+- Crisis support without deflection
+- Empathetic conversation
+## Files
+| File | Size | Device |
+|------|------|--------|
+| model.safetensors | 8 GB | Training/fine-tuning |
+| Luna-4B-thinking-Q4_K_M.gguf | 2.5 GB | GTX 1050 Ti |
+| Luna-4B-thinking-Q3_K_M.gguf | 1.8 GB | iPhone 15 (recommended) |
+| Luna-4B-thinking-Q2_K.gguf | 1.3 GB | iPhone 15 compact |
+| Luna-4B-thinking-Q8_0.gguf | 4.5 GB | High-end GPUs |
+## Usage
+### iPhone 15
+Download Q3_K_M.gguf, use with LM Studio iOS.
+### Desktop (GTX 1050 Ti)
+```python
+from llama_cpp import Llama
+llm = Llama(
+    model_path="Luna-4B-thinking-Q4_K_M.gguf",
+    n_ctx=2048,
+    n_gpu_layers=35
+)
+response = llm.create_chat_completion(
+    messages=[{"role": "user", "content": "I feel depressed"}],
+    max_tokens=1024
+)
+print(response["choices"][0]["message"]["content"])
+```
+## Training
+- 8-stage curriculum learning
+- LoRA (r=64, alpha=16)
+- ~60,000 mental health conversations
+- 20% replay buffers to prevent catastrophic forgetting
+- Kaggle dual T4 GPUs
+## Disclaimer
+Research model only. Not a replacement for professional medical advice.
+## License
+Apache 2.0