Update README.md

README.md

@@ -1,18 +1,13 @@
 ---
-
 base_model:
-  - happzy2633/qwen2.5-7b-ins-v3
-  - bunnycore/Qwen2.5-7B-Matrix
-  - bunnycore/Qwen2.5-7B-HyperMix
+- Qwen/Qwen2.5-7B-Instruct
 library_name: transformers
 tags:
-  - mergekit
-  - merge
-  - reasoning
-  - qwen
+- reasoning
+- qwen
 license: apache-2.0
 language:
-  - en
+- en
 pipeline_tag: text-generation
 model-index:
 - name: Qwen2.5-7B-Anvita
@@ -30,7 +25,8 @@ model-index:
       value: 64.33
       name: strict accuracy
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -45,7 +41,8 @@ model-index:
       value: 35.48
       name: normalized accuracy
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -60,7 +57,8 @@ model-index:
       value: 15.86
       name: exact match
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -75,7 +73,8 @@ model-index:
       value: 10.29
       name: acc_norm
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -90,7 +89,8 @@ model-index:
       value: 13.47
       name: acc_norm
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
       name: Open LLM Leaderboard
   - task:
       type: text-generation
@@ -107,26 +107,11 @@ model-index:
       value: 35.17
       name: accuracy
     source:
-      url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
+      url: >-
+        https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=sethuiyer/Qwen2.5-7B-Anvita
       name: Open LLM Leaderboard
-
 ---
 
-# **Qwen 2.5-7B Anvita**
-
-<img src="./logo.webp" alt="Logo" height="256px" width="256px" />
-
-## Overview
-
-**Anvita** is a reasoning-oriented AI model designed to **connect ideas** and **understand complex inputs**. Derived from the Sanskrit word meaning "connected" or "understood," Anvita embodies intellectual depth and comprehension, making it an ideal choice for tasks requiring nuanced understanding and sophisticated reasoning.
-
-Built using the **DARE TIES** merge method, Anvita integrates multiple pre-trained language models, including:
-
-- **Qwen2.5-7B-HyperMix**
-- **bunnycore/Qwen2.5-7B-Matrix**
-- **happzy2633/qwen2.5-7b-ins-v3**
-
-This combination optimizes Anvita for superior reasoning, dynamic conversations, and high-quality text generation.
 
 ## Evaluation Results
 | **Metric**              | **Value** |
@@ -141,85 +126,3 @@ This combination optimizes Anvita for superior reasoning, dynamic conversations,
 
 Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/results/blob/main/sethuiyer/Qwen2.5-7B-Anvita/results_2024-10-27T11-40-06.834908.json).
 Personal Benchmarks - check [PERSONAL_BENCHMARK.md](./PERSONAL_BENCHMARK.md)
-
-For optimal reasoning performance, it is recommended to use **BF16** precision and the [Entropic Chain of Thought](https://huggingface.co/sethuiyer/Qwen2.5-7B-Anvita/blob/main/entropic_cot.py) decoding method. This experimental decoder combines entropy and CoT decoding to enhance output quality.
-
-## Features
-
-- **Enhanced Reasoning:** Optimized for multi-step reasoning across various domains.
-- **Long Sequence Handling:** Capable of processing extended inputs without loss of context.
-- **Conversational Fluency:** Engages in fluid, context-aware dialogues.
-- **Dense Knowledge Integration:** Combines knowledge from multiple base models for comprehensive understanding.
-
-## Installation
-
-To get started with Anvita, ensure you have the necessary dependencies installed. You can use the [Transformers](https://huggingface.co/docs/transformers/index) library for seamless integration.
-
-```bash
-pip install transformers rich
-```
-
-## Quick Start
-
-Here's a simple example to demonstrate how to use Anvita for generating responses with enhanced reasoning capabilities.
-
-```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
-from rich.console import Console
-from rich.markdown import Markdown
-
-# Initialize console
-console = Console()
-
-# Load the tokenizer and model from the specified path
-MODEL_PATH = "sethuiyer/Qwen2.5-7B-Anvita"
-
-tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
-model = AutoModelForCausalLM.from_pretrained(MODEL_PATH).to("cuda")
-
-QUESTION = "Is 9.11 greater than 9.8?"
-
-messages = [
-    {"role": "user", "content": QUESTION}
-]
-
-# Generate the answer using Entropic Chain of Thought decoding
-answer, score = cot_decode_speculative(model, tokenizer, messages, k=2, max_new_tokens=2058)
-
-# Format the answer as markdown
-markdown_answer = f"""
-# **Answer:**  
-{answer}
-
-**Score:** {score}
-"""
-
-# Display the answer in markdown format
-console.print(Markdown(markdown_answer))
-```
-
-## Configuration
-
-The following YAML configuration was used to produce Anvita:
-
-```yaml
-slices:
-  models:
-    - model: bunnycore/Qwen2.5-7B-Matrix
-      parameters:
-        weight: [0.25, 0.35, 0.45, 0.35, 0.25]
-        density: [0.1, 0.25, 0.5, 0.25, 0.1]
-    - model: bunnycore/Qwen2.5-7B-HyperMix
-    - model: happzy2633/qwen2.5-7b-ins-v3
-      parameters:
-        weight: [0.55, 0.45, 0.35, 0.45, 0.55]
-        density: [0.1, 0.25, 0.5, 0.25, 0.1]
-merge_method: dare_ties
-base_model: bunnycore/Qwen2.5-7B-HyperMix
-parameters:
-  int8_mask: true
-dtype: bfloat16
-```
-
-
-