README.md

---
license: llama3
language:
- en
- zh
base_model: prithivMLmods/Deepthink-Llama-3-8B-Preview
pipeline_tag: text-generation
library_name: transformers
tags:
- text-generation-inference
- llama-cpp
- gguf-my-repo
---

# Triangle104/Deepthink-Llama-3-8B-Preview-Q4_K_M-GGUF
This model was converted to GGUF format from [`prithivMLmods/Deepthink-Llama-3-8B-Preview`](https://huggingface.co./prithivMLmods/Deepthink-Llama-3-8B-Preview) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co./spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co./prithivMLmods/Deepthink-Llama-3-8B-Preview) for more details on the model.

---
The Deepthink-Llama-3-8B-Preview is a fine-tuned version of the Llama-3.1-8B base model, further enhanced with the Rethinking R1 Dataset Logits
 for superior text generation. This model is designed for advanced 
reasoning, structured problem-solving, and contextually rich outputs, 
making it an excellent choice for applications in education, programming, research, and creative writing.  


With its optimized architecture, Deepthink-Llama-3-8B-Preview excels at:  


Logical reasoning and step-by-step problem solving  
Mathematical and coding tasks, leveraging specialized expert models  
Generating long-form content (up to 8K tokens) with improved coherence  
Understanding structured data, including tables and JSON outputs  
Instruction following and adapting to diverse system prompts, making it ideal for chatbots and AI assistants



	
		
	

		Key Features
	



Supports long-context processing of up to 128K tokens  
Multilingual capabilities for 29+ languages, including English, Chinese, Spanish, French, German, Arabic, and more  
Fine-tuned using Supervised Fine-Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF)



	
		
	

		Model Architecture
	



Deepthink-Llama-3-8B-Preview is built on the optimized transformer architecture of Llama-3.1-8B, integrating enhanced dataset logits from Rethinking R1 for better contextual understanding and output quality.  



	
		
	

		Use with transformers
	



To run conversational inference using transformers >= 4.43.0, use the pipeline abstraction or leverage the generate() function with the Auto classes.  


Ensure your environment is updated with:  


pip install --upgrade transformers




	
		
	

		Example Usage
	



import torch
from transformers import pipeline

model_id = "prithivMLmods/Deepthink-Llama-3-8B-Preview"
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])




	
		
	

		Intended Use
	



Deepthink-Llama-3-8B-Preview is designed for a wide 
range of applications requiring deep reasoning, structured outputs, and 
logical text generation. It is particularly suited for:  


Education & Research: Generating detailed explanations, step-by-step solutions, and structured academic content.  
Programming & Code Generation: Assisting in code writing, debugging, and algorithm explanations with improved logic structuring.  
AI Chatbots & Assistants: Providing context-aware, instruction-following responses for conversational AI applications.  
Creative Writing: Generating high-quality stories, articles, and structured narratives with coherence.  
Data Analysis & Structured Output Generation: Interpreting and generating JSON, tables, and formatted outputs for structured data processing.



	
		
	

		Limitations
	



While Deepthink-Llama-3-8B-Preview is optimized for deep reasoning and structured outputs, it has some limitations:  


Not a Real-time Knowledge Source  


The model is trained on a fixed dataset and does not have real-time 
internet access. It may not provide up-to-date information on rapidly 
evolving topics.


Potential Biases  


As with all AI models, responses may reflect biases present in the 
training data. Users should critically evaluate outputs, especially in 
sensitive domains.


Mathematical & Logical Reasoning Constraints  


While strong in step-by-step reasoning, it may occasionally produce 
incorrect mathematical calculations or logical inconsistencies. External
 verification is recommended for critical applications.


Handling of Extremely Long Contexts  


While it supports up to 128K tokens, efficiency and coherence may degrade when processing very long documents or conversations.


Limited Handling of Ambiguity  


The model may struggle with highly ambiguous or context-dependent 
queries, sometimes generating plausible but incorrect responses.


Ethical & Compliance Considerations  


Not intended for generating misinformation, automating legal or 
medical decisions, or other high-risk applications without human 
oversight.

---
## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)

```bash
brew install llama.cpp

```
Invoke the llama.cpp server or the CLI.

### CLI:
```bash
llama-cli --hf-repo Triangle104/Deepthink-Llama-3-8B-Preview-Q4_K_M-GGUF --hf-file deepthink-llama-3-8b-preview-q4_k_m.gguf -p "The meaning to life and the universe is"
```

### Server:
```bash
llama-server --hf-repo Triangle104/Deepthink-Llama-3-8B-Preview-Q4_K_M-GGUF --hf-file deepthink-llama-3-8b-preview-q4_k_m.gguf -c 2048
```

Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.
```
git clone https://github.com/ggerganov/llama.cpp
```

Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
```
cd llama.cpp && LLAMA_CURL=1 make
```

Step 3: Run inference through the main binary.
```
./llama-cli --hf-repo Triangle104/Deepthink-Llama-3-8B-Preview-Q4_K_M-GGUF --hf-file deepthink-llama-3-8b-preview-q4_k_m.gguf -p "The meaning to life and the universe is"
```
or 
```
./llama-server --hf-repo Triangle104/Deepthink-Llama-3-8B-Preview-Q4_K_M-GGUF --hf-file deepthink-llama-3-8b-preview-q4_k_m.gguf -c 2048
```