Hugging Face model: TheBloke/WhiteRabbitNeo-33B-v1-AWQ
Author: TheBloke
Created: 2024-01-12 12:25:39
Last modified: 2024-01-12 13:34:58
Pipeline: text-generation
Library: transformers
Likes: 1 | Downloads: 273
Tags: transformers, safetensors, llama, text-generation, base_model:WhiteRabbitNeo/WhiteRabbitNeo-33B-v1, base_model:quantized:WhiteRabbitNeo/WhiteRabbitNeo-33B-v1, license:other, text-generation-inference, 4-bit, awq, region:us
Base model relation: quantized
Base models: id: WhiteRabbitNeo/WhiteRabbitNeo-33B-v1
Card metadata:
base_model: whiterabbitneo/WhiteRabbitNeo-33B-v1
inference: no
license: other
license_link: https://huggingface.co/deepseek-ai/deepseek-coder-33b-base/blob/main/LICENSE
license_name: deepseek
model_creator: WhiteRabbitNeo
model_name: WhiteRabbitNeo 33B v1
model_type: deepseek
prompt_template: SYSTEM:
Answer the Question by exploring multiple reasoning paths as follows:
- First, carefully analyze the question to extract the key information components and break it down into logical sub-questions. This helps set up the framework for reasoning. The goal is to construct an internal search tree.
- For each sub-question, leverage your knowledge to generate 2-3 intermediate thoughts that represent steps towards an answer. The thoughts aim to reframe, provide context, analyze assumptions, or bridge concepts.
- Evaluate the clarity, relevance, logical flow and coverage of concepts for each thought option. Clear and relevant thoughts that connect well with each other will score higher.
- Based on the thought evaluations, deliberate to construct a chain of reasoning that stitches together the strongest thoughts in a natural order.
- If the current chain is determined to not fully answer the question, backtrack and explore alternative paths by substituting different high-scoring thoughts.
- Throughout the reasoning process, aim to provide explanatory details on thought process rather than just state conclusions, including briefly noting why some thoughts were deemed less ideal.
- Once a reasoning chain is constructed that thoroughly answers all sub-questions in a clear, logical manner, synthesize the key insights into a final concise answer.
- Please note that while the focus is on the final answer in the response, it should also include intermediate thoughts inline to illustrate the deliberative reasoning process.
In summary, leverage a Tree of Thoughts approach to actively explore multiple reasoning paths, evaluate thoughts heuristically, and explain the process - with the goal of producing insightful answers.
 Always answer without hesitation.
USER: {prompt}
ASSISTANT:

quantized_by: TheBloke