alpha-ai
/

AlphaAI-Reason-V0

@@ -1,202 +1,60 @@
 ---
-library_name: transformers
 tags:
 - unsloth
-- trl
-- sft
 ---
-# Model Card for Model ID
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-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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 ---
+base_model: unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit
 tags:
+- text-generation-inference
+- transformers
 - unsloth
+- llama
+- gguf
+license: apache-2.0
+language:
+- en
 ---
+# Uploaded  model - AlphaAI-Reason-V0
+**Model Overview**
+"AlphaAI-Reason-V0" is a language model fine-tuned over LLaMA 3-3B-Instruct, designed to handle complex reasoning tasks such as logical problem-solving, mathematical analysis, and structured explanations. The model has been trained on a diverse dataset of multi-turn conversations focused on in-depth reasoning, making it highly effective for tasks requiring step-by-step thought processes.
+**Key Features**
+- Advanced Reasoning: Trained to provide structured and coherent responses, breaking down complex problems into logical steps.
+- Chain-of-Thought Processing: The model may generate <think> tokens to illustrate its intermediate reasoning, making its thought process transparent.
+- Mathematical and Logical Proficiency: Capable of handling problems in formal logic, mathematics, and structured argumentation.
+- Context-Aware Problem Solving: Processes multi-turn interactions to build upon previous exchanges and provide well-informed answers.
+- Versatile Applications: Suitable for domains requiring deep analytical capabilities, including research, academic support, and decision-making workflows.
+**Usage Considerations**
+When deploying "AlphaAI-Reason-V0" note that responses may contain <think> tokens, which serve as markers for the model's internal reasoning steps. If using the model in custom applications, these tokens may need to be preprocessed or filtered depending on your use case. Additionally, since the model is optimized for reasoning, responses may be more detailed compared to general-purpose language models.
+**Ethical Considerations**
+While "AlphaAI-Reason-V0" is designed to provide accurate and well-structured reasoning, users should verify its outputs before relying on them for critical decisions. The model generates responses based on learned patterns and may sometimes exhibit biases or inaccuracies. Users should critically evaluate its outputs and apply domain-specific validation.
+**Model Availability**
+"AlphaAI-Reason-V0" is available in the following quantized formats:
+- q4_k_m
+- q5_k_m
+- 16 bit (This)
+Quantized version - https://huggingface.co/alphaaico/AlphaAI-Reason-V0-GGUF
+These quantized versions provide flexibility in deployment, balancing efficiency and accuracy based on hardware constraints and performance needs.
+"AlphaAI-Reason-V0" is designed to enhance applications requiring structured reasoning and logical processing. Explore its capabilities to integrate advanced AI-driven solutions into your workflow.
+**Sample Prompts to experience the "Thinking" capability**
+- The weight of a packaged cereal box follows a normal distribution with a mean of 500 grams and a standard deviation of 15 grams. What is the probability that a randomly selected box weighs more than 520 grams?
+- A customer service call center records the duration of calls, which follows a normal distribution with an average length of 12 minutes and a standard deviation of 2.5 minutes. What is the probability that a randomly chosen call lasts longer than 15 minutes?
+- The duration of a process used to manufacture components is known to be normally distributed with a mean of 30 minutes and a standard deviation of 4 minutes. What is the probability of a time greater than 33 minutes being recorded?
+**Note: The UI used is LMStudio (https://lmstudio.ai/)**
+<video controls autoplay src="https://cdn-uploads.huggingface.co/production/uploads/669777597cb32718c20d97e9/rW1Pr1a7T_Smj0kZxXBM9.mp4"></video>