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Llama-Deepsync-1B/README.md

@@ -0,0 +1,108 @@
+---
+license: creativeml-openrail-m
+language:
+- en
+- de
+- fr
+- it
+- pt
+- hi
+- es
+- th
+base_model:
+- meta-llama/Llama-3.2-1B-Instruct
+pipeline_tag: text-generation
+tags:
+- text-generation-inference
+- Llama
+- Code
+- CoT
+- Math
+- Deepsync
+- 3b
+library_name: transformers
+---
+<pre align="center">
+    .___                                                 _______.    
+  __| _/____   ____ ______  _________.__. ____   ____   /_   \_ |__  
+ / __ |/ __ \_/ __ \\____ \/  ___<   |  |/    \_/ ___\   |   || __ \ 
+/ /_/ \  ___/\  ___/|  |_> >___ \ \___  |   |  \  \___   |   || \_\ \
+\____ |\___  >\___  >   __/____  >/ ____|___|  /\___  >  |___||___  /
+     \/    \/     \/|__|       \/ \/         \/     \/            \/ 
+</pre>
+
+The **Llama-Deepsync-1B** is a fine-tuned version of the **Llama-3.2-1B-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, **Llama-Deepsync-1B** 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. 
+
+- Significantly **more knowledge** and has greatly improved capabilities in **coding** and **mathematics**, thanks to our specialized expert models in these domains.
+- Significant improvements in **instruction following**, **generating long texts** (over 8K tokens), **understanding structured data** (e.g, tables), and **generating structured outputs** especially JSON. **More resilient to the diversity of system prompts**, enhancing role-play implementation and condition-setting for chatbots.
+- **Long-context Support** up to 128K tokens and can generate up to 8K tokens.
+- **Multilingual support** for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more. 
+
+# **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.
+
+# **Use with transformers**
+
+Starting with `transformers >= 4.43.0` onward, you can run conversational inference using the Transformers `pipeline` abstraction or by leveraging the Auto classes with the `generate()` function.
+
+Make sure to update your transformers installation via `pip install --upgrade transformers`.
+
+```python
+import torch
+from transformers import pipeline
+
+model_id = "prithivMLmods/Llama-Deepsync-1B"
+pipe = pipeline(
+    "text-generation",
+    model=model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+messages = [
+    {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
+    {"role": "user", "content": "Who are you?"},
+]
+outputs = pipe(
+    messages,
+    max_new_tokens=256,
+)
+print(outputs[0]["generated_text"][-1])
+```
+
+Note: You can also find detailed recipes on how to use the model locally, with `torch.compile()`, assisted generations, quantised and more at [`huggingface-llama-recipes`](https://github.com/huggingface/huggingface-llama-recipes)
+
+# **Run with Ollama [Ollama Run]**
+
+Ollama makes running machine learning models simple and efficient. Follow these steps to set up and run your GGUF models quickly.
+
+## Quick Start: Step-by-Step Guide
+
+| Step | Description                                     | Command / Instructions                                                                                                                                   |
+|------|-------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------|
+| 1    | **Install Ollama 🦙**                          | Download Ollama from [https://ollama.com/download](https://ollama.com/download) and install it on your system.                                            |
+| 2    | **Create Your Model File**                     | - Create a file named after your model, e.g., `metallama`.                                                                                               |
+|      |                                                 | - Add the following line to specify the base model:                                                                                                      |
+|      |                                                 |   ```bash                                                                                                                                               |
+|      |                                                 |   FROM Llama-3.2-1B.F16.gguf                                                                                                                            |
+|      |                                                 |   ```                                                                                                                                                   |
+|      |                                                 | - Ensure the base model file is in the same directory.                                                                                                   |
+| 3    | **Create and Patch the Model**                 | Run the following commands to create and verify your model:                                                                                             |
+|      |                                                 | ```bash                                                                                                                                                 |
+|      |                                                 | ollama create metallama -f ./metallama                                                                                                                  |
+|      |                                                 | ollama list                                                                                                                                             |
+|      |                                                 | ```                                                                                                                                                     |
+| 4    | **Run the Model**                              | Use the following command to start your model:                                                                                                          |
+|      |                                                 | ```bash                                                                                                                                                 |
+|      |                                                 | ollama run metallama                                                                                                                                    |
+|      |                                                 | ```                                                                                                                                                     |
+| 5    | **Interact with the Model**                    | Once the model is running, interact with it:                                                                                                            |
+|      |                                                 | ```plaintext                                                                                                                                             |
+|      |                                                 | >>> Tell me about Space X.                                                                                                                              |
+|      |                                                 | Space X, the private aerospace company founded by Elon Musk, is revolutionizing space exploration...                                                    |
+|      |                                                 | ```                                                                                                                                                     |
+
+## Conclusion
+With Ollama, running and interacting with models is seamless. Start experimenting today!

README.md

@@ -0,0 +1,17 @@
+
+---
+license: mit
+language:
+- en
+pipeline_tag: text-generation
+---
+
+My own (ZeroWw) quantizations.
+output and embed tensors quantized to f16.
+all other tensors quantized to q5_k or q6_k.
+
+Result:
+both f16.q6 and f16.q5 are smaller than q8_0 standard quantization
+and they perform as well as the pure f16.
+
+Updated on: Tue Jan 14, 14:11:53