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README.md

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+
+---
+
+license: creativeml-openrail-m
+pipeline_tag: text-generation
+library_name: transformers
+language:
+- en
+base_model:
+- meta-llama/Llama-3.2-3B-Instruct
+tags:
+- codepy
+- safetensors
+- ollama
+- llama-cpp
+- trl
+- deep-think
+- coder
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
+
+
+# QuantFactory/Codepy-Deepthink-3B-GGUF
+This is quantized version of [prithivMLmods/Codepy-Deepthink-3B](https://huggingface.co/prithivMLmods/Codepy-Deepthink-3B) created using llama.cpp
+
+# Original Model Card
+
+# **Codepy 3B Deep Think Model File**
+
+The **Codepy 3B Deep Think Model** is a fine-tuned version of the **meta-llama/Llama-3.2-3B-Instruct** base model, designed for text generation tasks that require deep reasoning, logical structuring, and problem-solving. This model leverages its optimized architecture to provide accurate and contextually relevant outputs for complex queries, making it ideal for applications in education, programming, and creative writing. 
+
+With its robust natural language processing capabilities, **Codepy 3B Deep Think** excels in generating step-by-step solutions, creative content, and logical analyses. Its architecture integrates advanced understanding of both structured and unstructured data, ensuring precise text generation aligned with user inputs. 
+
+| **Model Content**                     | **Size**       | **Description**                                 | **Upload Status** |
+|-----------------------------------|----------------|------------------------------------------------|-------------------|
+| `.gitattributes`                  | 1.57 kB        | Git LFS configuration for large files.          | Uploaded          |
+| `README.md`                       | 221 Bytes      | Basic repository information.                   | Updated           |
+| `config.json`                     | 994 Bytes      | Model configuration with architectural details. | Uploaded          |
+| `generation_config.json`          | 248 Bytes      | Default generation parameters.                  | Uploaded          |
+| `pytorch_model-00001-of-00002.bin`| 4.97 GB        | Sharded PyTorch model weights (part 1 of 2).    | Uploaded (LFS)    |
+| `pytorch_model-00002-of-00002.bin`| 1.46 GB        | Sharded PyTorch model weights (part 2 of 2).    | Uploaded (LFS)    |
+| `pytorch_model.bin.index.json`    | 21.2 kB        | Index file mapping model shards.                | Uploaded          |
+| `special_tokens_map.json`         | 477 Bytes      | Maps special tokens to their respective IDs.    | Uploaded          |
+| `tokenizer.json`                  | 17.2 MB        | Full tokenizer vocabulary and merges.           | Uploaded (LFS)    |
+| `tokenizer_config.json`           | 57.5 kB        | Tokenizer configuration details.                | Uploaded          |
+
+| Run with LM Studio       | Details                                                                                       |
+|--------------------------|-----------------------------------------------------------------------------------------------|
+| *Run with LM Studio*   | https://lmstudio.ai/                                                         |
+| *Demo on LM Studio*    | https://drive.google.com/file/d/1CHdfjYrwMnk9ACvS40Abfy3xNXnCubKG/view?usp=sharing |
+| *Codepy-Deepthink-3B-GGUF* | https://huggingface.co/prithivMLmods/Codepy-Deepthink-3B-GGUF |
+
+---
+# **<span style="color:red;">Sample Deepthink Inference</span>**
+
+>>> Develop a Python program to generate random passwords that consist of 8 characters. Not applicable
+
+```markdown
+# Random Password Generator
+
+This Python program generates a random password of a specified length (default: 8 characters) that includes a mix of lowercase letters, uppercase letters, digits, and spaces. The program ensures the generated password meets basic security requirements while maintaining simplicity.
+
+## Features
+- Generates alphanumeric passwords with optional spaces.
+- Ensures at least one lowercase letter, one uppercase letter, one digit, and one space in the password.
+- Shuffles the characters to randomize the order.
+- Includes error handling for invalid input lengths.
+
+## Requirements
+- Python 3.x
+
+## Usage
+1. Clone or download this repository.
+2. Run the script using Python:
+
+   ```bash
+   python password_generator.py
+   ```
+
+3. The script will generate and print an 8-character random password to the console.
+
+## Code
+
+```python
+import random
+
+def generate_password(length):
+    """
+    Generates a random alphanumeric password of the specified length.
+
+    Ensures that at least one lowercase letter, one uppercase letter,
+    one digit, and one space are included in the password.
+
+    Args:
+        length: The number of characters in the password.
+
+    Returns:
+        A string representing the generated password or None if the input is invalid.
+    """
+
+    # Define a set of alphanumeric characters with spaces
+    characters = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789 '
+
+    # Validate the length
+    if length < 1:
+        return None
+
+    # Handle invalid length
+    if length > len(characters):
+        print("Invalid password length. It should be less than or equal to", len(characters))
+        return None
+
+    # Ensure at least one character from each required group
+    required_characters = 'abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789 '
+    if length > 1:
+        password_length_without_requirements = length - 4
+        random_string = ''.join(random.choice(required_characters) for _ in range(password_length_without_requirements))
+
+    # Fill the rest of the password with random characters
+    remaining_chars_needed = length - len(random_string)
+    all_possible_chars = list(characters)
+    if length > 1:
+        random_character = random.choice('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789 ')
+    else:
+        random_character = random.choice('abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789 ')
+
+    password = random_string + random_character * remaining_chars_needed
+
+    # Shuffle the password to avoid predictable patterns
+    password_list = list(password)
+    random.shuffle(password_list)
+    password = ''.join(password_list)
+
+    return password
+
+# Example Usage
+password_length = 8
+generated_password = generate_password(password_length)
+
+if generated_password is not None:
+    print(f"Generated Password: {generated_password}")
+else:
+    print("Failed to generate a password. Please ensure the length is valid (between 1 and", len(characters), ").")
+```
+
+## Example Output
+```
+Generated Password: g7x 2PqA
+```
+
+## Customization
+To customize the password length, modify the `password_length` variable in the script.
+
+## Security Notes
+- This implementation uses Python's `random` module, which is suitable for general-purpose randomness. For cryptographically secure passwords, consider using the `secrets` module.
+- The character set includes spaces for additional complexity, but you can modify the `characters` string to include other symbols (e.g., `!@#$%^&*`).
+---
+# **Model Architecture**
+
+ Llama 3.2 is an auto-regressive language model that uses an optimized transformer architecture. The tuned versions use supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) to align with human preferences for helpfulness and safety.
+
+# **Run with Ollama [ Ollama Run ]**
+
+Ollama simplifies running machine learning models. This guide walks you through downloading, installing, and running GGUF models in minutes.
+
+## Table of Contents
+
+- [Download and Install](#download-and-install)
+- [Run GGUF Models](#run-gguf-models)
+- [Running the Model](#running-the-model)
+- [Sample Usage](#sample-usage)
+
+## Download and Install
+
+Download Ollama from [https://ollama.com/download](https://ollama.com/download) and install it on your Windows or Mac system.
+
+## Run GGUF Models
+
+1. **Create the Model File**  
+   Create a model file, e.g., `metallama`.
+
+2. **Add the Template Command**  
+   Include a `FROM` line in the file to specify the base model:  
+   ```bash
+   FROM Llama-3.2-1B.F16.gguf
+   ```
+
+3. **Create and Patch the Model**  
+   Run the following command:  
+   ```bash
+   ollama create metallama -f ./metallama
+   ```  
+   Verify the model with:  
+   ```bash
+   ollama list
+   ```
+
+## Running the Model
+
+Run your model with:  
+```bash
+ollama run metallama
+```
+
+### Sample Usage
+
+Interact with the model:  
+```plaintext
+>>> write a mini passage about space x
+Space X, the private aerospace company founded by Elon Musk, is revolutionizing the field of space exploration...
+```
+
+---
+
+With these steps, you can easily run custom models using Ollama. Adjust as needed for your specific use case.