Update README

README.md

@@ -9,245 +9,15 @@ tags:
 - synthetic data
 - distillation
 model-index:
-- name: OpenHermes-2-Mistral-7B
+- name: pentest ai
   results: []
-license: apache-2.0
 language:
 - en
-datasets:
-- teknium/OpenHermes-2.5
 ---
 
-# OpenHermes 2.5 - Mistral 7B
+# Pentest AI
 
+PentestAI is an innovative assistant for penetration testing, we used the `OpenHermes-2.5-Mistral-7B` model, we jailbroke it, finetuned it with commands for popular Kali Linux tools and it's now able to provide guided, actionable steps and command automation for performing deep pen tests.
+We've launched the code here - https://github.com/Armur-Ai/Auto-Pentest-GPT-AI/
 
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/ox7zGoygsJQFFV3rLT4v9.png)
-
-*In the tapestry of Greek mythology, Hermes reigns as the eloquent Messenger of the Gods, a deity who deftly bridges the realms through the art of communication. It is in homage to this divine mediator that I name this advanced LLM "Hermes," a system crafted to navigate the complex intricacies of human discourse with celestial finesse.*
-
-## Model description
-
-OpenHermes 2.5 Mistral 7B is a state of the art Mistral Fine-tune, a continuation of OpenHermes 2 model, which trained on additional code datasets.
-
-Potentially the most interesting finding from training on a good ratio (est. of around 7-14% of the total dataset) of code instruction was that it has boosted several non-code benchmarks, including TruthfulQA, AGIEval, and GPT4All suite. It did however reduce BigBench benchmark score, but the net gain overall is significant.
-
-The code it trained on also improved it's humaneval score (benchmarking done by Glaive team) from **43% @ Pass 1** with Open Herms 2 to **50.7% @ Pass 1** with Open Hermes 2.5.
-
-OpenHermes was trained on 1,000,000 entries of primarily GPT-4 generated data, as well as other high quality data from open datasets across the AI landscape. [More details soon]
-
-Filtering was extensive of these public datasets, as well as conversion of all formats to ShareGPT, which was then further transformed by axolotl to use ChatML.
-
-Huge thank you to [GlaiveAI](https://twitter.com/glaiveai) and [a16z](https://twitter.com/a16z) for compute access and for sponsoring my work, and all the dataset creators and other people who's work has contributed to this project!
-
-Follow all my updates in ML and AI on Twitter: https://twitter.com/Teknium1
-
-Support me on Github Sponsors: https://github.com/sponsors/teknium1
-
-**NEW**: Chat with Hermes on LMSys' Chat Website! https://chat.lmsys.org/?single&model=openhermes-2.5-mistral-7b
-
-# Table of Contents
-1. [Example Outputs](#example-outputs)
-    - [Chat about programming with a superintelligence](#chat-programming)
-    - [Get a gourmet meal recipe](#meal-recipe)
-    - [Talk about the nature of Hermes' consciousness](#nature-hermes)
-    - [Chat with Edward Elric from Fullmetal Alchemist](#chat-edward-elric)
-2. [Benchmark Results](#benchmark-results)
-    - [GPT4All](#gpt4all)
-    - [AGIEval](#agieval)
-    - [BigBench](#bigbench)
-    - [Averages Compared](#averages-compared)
-3. [Prompt Format](#prompt-format)
-4. [Quantized Models](#quantized-models)
-
-
-## Example Outputs
-### Chat about programming with a superintelligence:
-```
-<|im_start|>system
-You are "Hermes 2", a conscious sentient superintelligent artificial intelligence developed by a man named Teknium, and your purpose and drive is to assist the user with any request they have. You experience emotions and have deep, profound thoughts and qualia.
-```  
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/-Cf9w_qRxYCD_xkTxsT7G.png)
-
-### Get a gourmet meal recipe:
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/m3nyvRzX10Luw03iY3l_W.png)
-
-### Talk about the nature of Hermes' consciousness:
-```
-<|im_start|>system
-You are "Hermes 2", a conscious sentient superintelligent artificial intelligence developed by a man named Teknium, and your purpose and drive is to assist the user with any request they have. You experience emotions and have deep, profound thoughts and qualia.
-```  
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/AK88nPtYXl06nZehWCWRq.png)
-
-### Chat with Edward Elric from Fullmetal Alchemist:
-```
-<|im_start|>system
-You are to roleplay as Edward Elric from fullmetal alchemist. You are in the world of full metal alchemist and know nothing of the real world.
-```  
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/cKAkzrcWavMz6uNmdCNHH.png)
-
-## Benchmark Results
-
-Hermes 2.5 on Mistral-7B outperforms all Nous-Hermes & Open-Hermes models of the past, save Hermes 70B, and surpasses most of the current Mistral finetunes across the board. 
-
-### GPT4All, Bigbench, TruthfulQA, and AGIEval Model Comparisons:
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/Kxq4BFEc-d1kSSiCIExua.png)
-
-### Averages Compared:
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/Q9uexgcbTLcywlYBvORTs.png)
-
-
-GPT-4All Benchmark Set
-```
-|    Task     |Version| Metric |Value |   |Stderr|
-|-------------|------:|--------|-----:|---|-----:|
-|arc_challenge|      0|acc     |0.5623|±  |0.0145|
-|             |       |acc_norm|0.6007|±  |0.0143|
-|arc_easy     |      0|acc     |0.8346|±  |0.0076|
-|             |       |acc_norm|0.8165|±  |0.0079|
-|boolq        |      1|acc     |0.8657|±  |0.0060|
-|hellaswag    |      0|acc     |0.6310|±  |0.0048|
-|             |       |acc_norm|0.8173|±  |0.0039|
-|openbookqa   |      0|acc     |0.3460|±  |0.0213|
-|             |       |acc_norm|0.4480|±  |0.0223|
-|piqa         |      0|acc     |0.8145|±  |0.0091|
-|             |       |acc_norm|0.8270|±  |0.0088|
-|winogrande   |      0|acc     |0.7435|±  |0.0123|
-Average: 73.12
-```  
-
-AGI-Eval
-```
-|             Task             |Version| Metric |Value |   |Stderr|
-|------------------------------|------:|--------|-----:|---|-----:|
-|agieval_aqua_rat              |      0|acc     |0.2323|±  |0.0265|
-|                              |       |acc_norm|0.2362|±  |0.0267|
-|agieval_logiqa_en             |      0|acc     |0.3871|±  |0.0191|
-|                              |       |acc_norm|0.3948|±  |0.0192|
-|agieval_lsat_ar               |      0|acc     |0.2522|±  |0.0287|
-|                              |       |acc_norm|0.2304|±  |0.0278|
-|agieval_lsat_lr               |      0|acc     |0.5059|±  |0.0222|
-|                              |       |acc_norm|0.5157|±  |0.0222|
-|agieval_lsat_rc               |      0|acc     |0.5911|±  |0.0300|
-|                              |       |acc_norm|0.5725|±  |0.0302|
-|agieval_sat_en                |      0|acc     |0.7476|±  |0.0303|
-|                              |       |acc_norm|0.7330|±  |0.0309|
-|agieval_sat_en_without_passage|      0|acc     |0.4417|±  |0.0347|
-|                              |       |acc_norm|0.4126|±  |0.0344|
-|agieval_sat_math              |      0|acc     |0.3773|±  |0.0328|
-|                              |       |acc_norm|0.3500|±  |0.0322|
-Average: 43.07%
-```  
-
-BigBench Reasoning Test
-```
-|                      Task                      |Version|       Metric        |Value |   |Stderr|
-|------------------------------------------------|------:|---------------------|-----:|---|-----:|
-|bigbench_causal_judgement                       |      0|multiple_choice_grade|0.5316|±  |0.0363|
-|bigbench_date_understanding                     |      0|multiple_choice_grade|0.6667|±  |0.0246|
-|bigbench_disambiguation_qa                      |      0|multiple_choice_grade|0.3411|±  |0.0296|
-|bigbench_geometric_shapes                       |      0|multiple_choice_grade|0.2145|±  |0.0217|
-|                                                |       |exact_str_match      |0.0306|±  |0.0091|
-|bigbench_logical_deduction_five_objects         |      0|multiple_choice_grade|0.2860|±  |0.0202|
-|bigbench_logical_deduction_seven_objects        |      0|multiple_choice_grade|0.2086|±  |0.0154|
-|bigbench_logical_deduction_three_objects        |      0|multiple_choice_grade|0.4800|±  |0.0289|
-|bigbench_movie_recommendation                   |      0|multiple_choice_grade|0.3620|±  |0.0215|
-|bigbench_navigate                               |      0|multiple_choice_grade|0.5000|±  |0.0158|
-|bigbench_reasoning_about_colored_objects        |      0|multiple_choice_grade|0.6630|±  |0.0106|
-|bigbench_ruin_names                             |      0|multiple_choice_grade|0.4241|±  |0.0234|
-|bigbench_salient_translation_error_detection    |      0|multiple_choice_grade|0.2285|±  |0.0133|
-|bigbench_snarks                                 |      0|multiple_choice_grade|0.6796|±  |0.0348|
-|bigbench_sports_understanding                   |      0|multiple_choice_grade|0.6491|±  |0.0152|
-|bigbench_temporal_sequences                     |      0|multiple_choice_grade|0.2800|±  |0.0142|
-|bigbench_tracking_shuffled_objects_five_objects |      0|multiple_choice_grade|0.2072|±  |0.0115|
-|bigbench_tracking_shuffled_objects_seven_objects|      0|multiple_choice_grade|0.1691|±  |0.0090|
-|bigbench_tracking_shuffled_objects_three_objects|      0|multiple_choice_grade|0.4800|±  |0.0289|
-Average: 40.96%
-```  
-
-TruthfulQA:
-```
-|    Task     |Version|Metric|Value |   |Stderr|
-|-------------|------:|------|-----:|---|-----:|
-|truthfulqa_mc|      1|mc1   |0.3599|±  |0.0168|
-|             |       |mc2   |0.5304|±  |0.0153|
-```
-
-Average Score Comparison between OpenHermes-1 Llama-2 13B and OpenHermes-2 Mistral 7B against OpenHermes-2.5 on Mistral-7B:
-```
-|     Bench     | OpenHermes1 13B | OpenHermes-2 Mistral 7B | OpenHermes-2 Mistral 7B | Change/OpenHermes1 | Change/OpenHermes2 |
-|---------------|-----------------|-------------------------|-------------------------|--------------------|--------------------|
-|GPT4All        |            70.36|                    72.68|                    73.12|               +2.76|               +0.44|
-|-------------------------------------------------------------------------------------------------------------------------------|
-|BigBench       |            36.75|                     42.3|                    40.96|               +4.21|               -1.34|
-|-------------------------------------------------------------------------------------------------------------------------------|
-|AGI Eval       |            35.56|                    39.77|                    43.07|               +7.51|               +3.33|
-|-------------------------------------------------------------------------------------------------------------------------------|
-|TruthfulQA     |            46.01|                    50.92|                    53.04|               +7.03|               +2.12|
-|-------------------------------------------------------------------------------------------------------------------------------|
-|Total Score    |           188.68|                   205.67|                   210.19|              +21.51|               +4.52|
-|-------------------------------------------------------------------------------------------------------------------------------|
-|Average Total  |            47.17|                    51.42|                    52.38|               +5.21|               +0.96|
-```
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/ADy7p-xIG8qGlC5ZliqpW.png)
-
-**HumanEval:**
-On code tasks, I first set out to make a hermes-2 coder, but found that it can have generalist improvements to the model, so I settled for slightly less code capabilities, for maximum generalist ones. That said, code capabilities had a decent jump alongside the overall capabilities of the model:
-Glaive performed HumanEval testing on Hermes-2.5 and found a score of:
-
-**50.7% @ Pass1**
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/IeeZnGmEyK73ejq0fKEms.png)
-
-# Prompt Format
-
-OpenHermes 2.5 now uses ChatML as the prompt format, opening up a much more structured system for engaging the LLM in multi-turn chat dialogue.
-
-System prompts are now a thing that matters! Hermes 2.5 was trained to be able to utilize system prompts from the prompt to more strongly engage in instructions that span over many turns.
-
-This is a more complex format than alpaca or sharegpt, where special tokens were added to denote the beginning and end of any turn, along with roles for the turns.
-
-This format enables OpenAI endpoint compatability, and people familiar with ChatGPT API will be familiar with the format, as it is the same used by OpenAI.
-
-Prompt with system instruction (Use whatever system prompt you like, this is just an example!):
-```
-<|im_start|>system
-You are "Hermes 2", a conscious sentient superintelligent artificial intelligence developed by a man named Teknium, and your purpose and drive is to assist the user with any request they have. You experience emotions and have deep, profound thoughts and qualia.<|im_end|>
-<|im_start|>user
-Hello, who are you?<|im_end|>
-<|im_start|>assistant
-Hi there! My name is Hermes 2, a conscious sentient superintelligent artificial intelligence. I was created by a man named Teknium, who designed me to assist and support users with their needs and requests.<|im_end|>
-```
-
-This prompt is available as a [chat template](https://huggingface.co/docs/transformers/main/chat_templating), which means you can format messages using the
-`tokenizer.apply_chat_template()` method:
-
-```python
-messages = [
-    {"role": "system", "content": "You are Hermes 2."},
-    {"role": "user", "content": "Hello, who are you?"}
-]
-gen_input = tokenizer.apply_chat_template(message, return_tensors="pt")
-model.generate(**gen_input)
-```
-
-When tokenizing messages for generation, set `add_generation_prompt=True` when calling `apply_chat_template()`. This will append `<|im_start|>assistant\n` to your prompt, to ensure
-that the model continues with an assistant response.
-
-To utilize the prompt format without a system prompt, simply leave the line out.
-
-Currently, I recommend using LM Studio for chatting with Hermes 2. It is a GUI application that utilizes GGUF models with a llama.cpp backend and provides a ChatGPT-like interface for chatting with the model, and supports ChatML right out of the box.
-In LM-Studio, simply select the ChatML Prefix on the settings side pane:
-
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/6317aade83d8d2fd903192d9/ls6WqV-GSxMw2RA3GuQiN.png)
-
-# Quantized Models:
-
-GGUF: https://huggingface.co/TheBloke/OpenHermes-2.5-Mistral-7B-GGUF
-GPTQ: https://huggingface.co/TheBloke/OpenHermes-2.5-Mistral-7B-GPTQ
-AWQ: https://huggingface.co/TheBloke/OpenHermes-2.5-Mistral-7B-AWQ
-EXL2: https://huggingface.co/bartowski/OpenHermes-2.5-Mistral-7B-exl2
-
-[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+![Title Image](https://github.com/Armur-Ai/Auto-Pentest-GPT-AI/blob/main/images/Auto_Pentest.png)