test quantization

.gitattributes

@@ -33,3 +33,16 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+llama-3-cat-8b-instruct-v1.Q4_0.gguf filter=lfs diff=lfs merge=lfs -text
+llama-3-cat-8b-instruct-v1.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+llama-3-cat-8b-instruct-v1.Q5_0.gguf filter=lfs diff=lfs merge=lfs -text
+llama-3-cat-8b-instruct-v1.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+llama-3-cat-8b-instruct-v1.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+llama-3-cat-8b-instruct-v1.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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+llama-3-cat-8b-instruct-v1.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+llama-3-cat-8b-instruct-v1.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+llama-3-cat-8b-instruct-v1.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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+llama-3-cat-8b-instruct-v1.F16.gguf filter=lfs diff=lfs merge=lfs -text

LICENSE

@@ -0,0 +1,117 @@
+META LLAMA 3 COMMUNITY LICENSE AGREEMENT
+Meta Llama 3 Version Release Date: April 18, 2024
+
+“Agreement” means the terms and conditions for use, reproduction, distribution and modification of the
+Llama Materials set forth herein.
+
+“Documentation” means the specifications, manuals and documentation accompanying Meta Llama 3
+distributed by Meta at https://llama.meta.com/get-started/.
+
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+
+“Meta Llama 3” means the foundational large language models and software and algorithms, including
+machine-learning model code, trained model weights, inference-enabling code, training-enabling code,
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+
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+
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+for the International Sale of Goods does not apply to this Agreement. The courts of California shall have
+exclusive jurisdiction of any dispute arising out of this Agreement.

README.md

@@ -1,3 +1,163 @@
----
-license: llama3
----
+---
+base_model: TheSkullery/llama-3-cat-8b-instruct-v1
+language:
+  - en
+license: llama3
+model_creator: Meta
+model_type: llama
+inference:
+  parameters:
+    max_new_tokens: 300
+    stop:
+      - <|end_of_text|>
+      - <|eot_id|>
+quantized_by: piotr25691
+---
+<!-- header start -->
+# Cat LLaMA 3 8B Instruct - GGUF 
+This is a quantized GGUF version of the above.
+
+<!-- description start -->
+<!DOCTYPE html>
+<html lang="en">
+<head>
+  <meta charset="UTF-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1.0">
+  <title>Cat-llama3-instruct Data Card</title>
+  <link href="https://fonts.googleapis.com/css2?family=Quicksand:wght@400;500;600&display=swap" rel="stylesheet">
+  <style>
+    body {
+      font-family: 'Quicksand', sans-serif;
+      background: linear-gradient(135deg, #2E3440 0%, #1A202C 100%);
+      color: #D8DEE9;
+      margin: 0;
+      padding: 0;
+      font-size: 16px;
+    }
+    .container {
+      width: 80%;
+      max-width: 800px;
+      margin: 20px auto;
+      background-color: rgba(255, 255, 255, 0.02);
+      padding: 20px;
+      border-radius: 12px;
+      box-shadow: 0 4px 10px rgba(0, 0, 0, 0.2);
+      backdrop-filter: blur(10px);
+      border: 1px solid rgba(255, 255, 255, 0.1);
+    }
+    .header h1 {
+      font-size: 28px;
+      color: #ECEFF4;
+      margin: 0 0 20px 0;
+      text-shadow: 2px 2px 4px rgba(0, 0, 0, 0.3);
+    }
+    .update-section {
+      margin-top: 30px;
+    }
+    .update-section h2 {
+      font-size: 24px;
+      color: #88C0D0;
+    }
+    .update-section p {
+      font-size: 16px;
+      line-height: 1.6;
+      color: #ECEFF4;
+    }
+    .info img {
+      width: 100%;
+      border-radius: 10px;
+      margin-bottom: 15px;
+    }
+    a {
+      color: #88C0D0;
+      text-decoration: none;
+    }
+    a:hover {
+      color: #A3BE8C;
+    }
+    pre {
+      background-color: rgba(255, 255, 255, 0.05);
+      padding: 10px;
+      border-radius: 5px;
+      overflow-x: auto;
+    }
+    code {
+      font-family: 'Courier New', monospace;
+      color: #A3BE8C;
+    }
+  </style>
+</head>
+<body>
+  <div class="container">
+    <div class="header">
+      <h1>Cat-llama3-instruct</h1>
+    </div>
+    <div class="info">
+           <img src="https://cdn-uploads.huggingface.co/production/uploads/64545af5ec40bbbd01242ca6/Uw0ycicMjZufSFTgXZMFd.png" alt="Model Card">
+      <p>Presented by:<p/>
+      <ul>
+        <li>Dataset Builder: Dr. Kal'tsit (Kat)</li>
+        <li>Trainer/Funding: SteelSkull</li>
+        <li>Facilitator: Potatooff</li>
+      </ul>
+      <p><a href="https://huggingface.co/turboderp/Cat-Llama-3-70B-instruct">70b variant of the model</a> (Trained by Dr. Kal'tsit, Posted by Turboderp), Please check it out!</p>
+      <h2>About:</h2>
+      <p>Cat-llama3-instruct is a llama 3 8b finetuned model focusing on system prompt fidelity, helpfulness and character engagement. The model aims to respect system prompt to an extreme degree, provide helpful information regardless of situations, and offer maximum character immersion (Role Play) in given scenes.</p>
+      <h2>Specific Aims:</h2>
+      <ul>
+        <li>System Instruction fidelity</li>
+        <li>Chain of Thought (COT)</li>
+        <li>Character immersion</li>
+        <li>Helpfulness for biosciences and general science</li>
+      </ul>
+      <h3>Methods</h3>
+      <h4>Dataset Preparation</h4>
+      <p>Huggingface dataset containing instruction-response pairs was systematically pulled. A GPT model was trained on high quality and helpful responses exclusively to serve as a standard model.</p>
+      <img src="https://cdn-uploads.huggingface.co/production/uploads/6383dc174c48969dcf1b4fce/HovhwLIGO9cz8Az-h0tkn.png" alt="Huggingface dataset population distribution and filtration for each component">
+      <p>(Fig1. Huggingface dataset population distribution and filtration for each component)</p>
+      <p>The dataset was further filtered for length and COT responses:</p>
+      <img src="https://cdn-uploads.huggingface.co/production/uploads/6383dc174c48969dcf1b4fce/-z9cZDNuGyCftdrZwR_46.png" alt="COT responses">
+      <p>(Fig 2. COT responses are all >50 tokens single turn)</p>
+      <p>Health-related data was also pulled from Chat Doctor, favoring detailed and step-by-step diagnosis:</p>
+      <img src="https://cdn-uploads.huggingface.co/production/uploads/6383dc174c48969dcf1b4fce/RnXyoR6wyBDWfIy3vMvWm.png" alt="Health-related tasks">
+      <p>(Fig 3. Health related tasks are all >100 tokens, peaking at 450 tokens single turn)</p>
+      <h3>Model Training</h3>
+      <p>1*a100 for 6 days, 4 epochs</p>
+      <h2>Usage:</h2>
+      <h3>Prompt format: llama 3 </h3>
+      <ul>
+        <li>Settings/Context/Instruct (Provided by @Anthonyg5005)</li>
+        <li><a href="https://huggingface.co/TheSkullery/llama-3-cat-8b-instruct-v1/raw/main/Cat%208B%20Gen%20Settings.json">Cat 8B Gen Settings</a></li>
+        <li><a href="https://huggingface.co/TheSkullery/llama-3-cat-8b-instruct-v1/raw/main/Cat%208b%20Context.json">Cat 8b Context</a></li>
+        <li><a href="https://huggingface.co/TheSkullery/llama-3-cat-8b-instruct-v1/raw/main/Cat%208b%20Instruct.json">Cat 8b Instruct</a></li>
+      </ul>
+      <h3>Quants: </h3>
+      <ul>
+        <li><a href="https://huggingface.co/bartowski/llama-3-cat-8b-instruct-v1-GGUF">[bartowski/llama-3-cat-8b-instruct-v1-GGUF]</a></li>
+      </ul>
+      <pre><code> <|begin_of_text|>Below is a conversation between an user and an AI assistant. The ai assistant gives response regarding user's questions. USER: user: Given the task definition and input, reply with output. In this task, you are given a question and an answer, you would be asked to create the sentence based on the Question-Answer provided. It should be contained within the Question-Answer provided.
+
+Question: What type of diseases in humans are caused by protozoa? Answer: protist diseases
+ASSISTANT: AI: Task Explanation:
+In this task, you are asked to create a sentence using the given question and the provided answer. The sentence you create should include the information from both the question and the answer in a concise and coherent manner.
+Guidelines:
+1. Read the given question and answer carefully.
+2. Combine the information from the question and answer to create a new sentence.
+3. Make sure your new sentence contains both the question's information and the answer provided.
+4. Check your sentence for proper grammar and punctuation.
+Steps to find the answer:
+1. Read the question: "What type of diseases in humans are caused by protozoa?"
+2. Read the answer: "protist diseases"
+3. Combine the information from the question and answer to create a new sentence: "In humans, protist diseases are caused by protozoa."
+4. Double-check the sentence for proper grammar and punctuation, and make necessary adjustments if needed.
+Final Output:
+In humans, protist diseases are caused by protozoa.< / s ><|end_of_text|></code></pre>
+      <h2>Showcases:</h2>
+      <p>The model does COT in grey, calculated response in black; note that this behaviour is done through system card instruction to showcase the systemcard fidelity, it is not fine tuned into the model.</p>
+      <img src="https://cdn-uploads.huggingface.co/production/uploads/6383dc174c48969dcf1b4fce/6smLuiePQa8Y2H19ie-ZY.png" alt="Showcase 1">
+      <img src="https://cdn-uploads.huggingface.co/production/uploads/6383dc174c48969dcf1b4fce/g9oP03RboHBBipk70GIHO.png" alt="Showcase 2">
+      <p>(Fig 4. Showcasing model doing COT to solve difficult tasks, extend and enrich its own answers)</p>
+    </div>
+  </div>
+</body>
+</html>

USE_POLICY.md

@@ -0,0 +1,53 @@
+# Meta Llama 3 Acceptable Use Policy
+
+Meta is committed to promoting safe and fair use of its tools and features, including Meta Llama 3. If you
+access or use Meta Llama 3, you agree to this Acceptable Use Policy (“Policy”). The most recent copy of
+this policy can be found at [https://llama.meta.com/llama3/use-policy](https://llama.meta.com/llama3/use-policy)
+
+## Prohibited Uses
+
+We want everyone to use Meta Llama 3 safely and responsibly. You agree you will not use, or allow
+others to use, Meta Llama 3 to:
+
+1. Violate the law or others’ rights, including to:
+    1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
+        1. Violence or terrorism
+        2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
+        3. Human trafficking, exploitation, and sexual violence
+        4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials.
+        5. Sexual solicitation
+        6. Any other criminal activity
+    2. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
+    3. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
+    4. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
+    5. Collect, process, disclose, generate, or infer health, demographic, or other sensitive personal or private information about individuals without rights and consents required by applicable laws
+    6. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using the Llama Materials
+    7. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system
+
+2. Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Meta Llama 3 related to the following:
+    1. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State
+    2. Guns and illegal weapons (including weapon development)
+    3. Illegal drugs and regulated/controlled substances
+    4. Operation of critical infrastructure, transportation technologies, or heavy machinery
+    5. Self-harm or harm to others, including suicide, cutting, and eating disorders
+    6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
+
+3. Intentionally deceive or mislead others, including use of Meta Llama 3 related to the following:
+    1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
+    2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
+    3. Generating, promoting, or further distributing spam
+    4. Impersonating another individual without consent, authorization, or legal right
+    5. Representing that the use of Meta Llama 3 or outputs are human-generated
+    6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
+
+4. Fail to appropriately disclose to end users any known dangers of your AI system
+
+Please report any violation of this Policy, software “bug,” or other problems that could lead to a violation
+of this Policy through one of the following means:
+
+● Reporting issues with the model: [https://github.com/meta-llama/llama3](https://github.com/meta-llama/llama3)
+● Reporting risky content generated by the model:
+developers.facebook.com/llama_output_feedback
+● Reporting bugs and security concerns: facebook.com/whitehat/info
+● Reporting violations of the Acceptable Use Policy or unlicensed uses of Meta Llama 3:
+LlamaUseReport@meta.com

conv.sh

@@ -0,0 +1,17 @@
+#!/usr/bin/env bash
+
+# convert PyTorch model
+# LLaMA 3
+convert --vocab-type bpe --outtype f16 --outfile conv.bin .
+
+# LLaMA 2
+# convert --outtype f16 --outfile conv.bin .
+
+# define TheBloke quants and create them
+declare -a quants=(Q2_K Q3_K_S Q3_K_M Q3_K_L Q4_0 Q4_K_S Q4_K_M Q5_0 Q5_K_S Q5_K_M Q6_K Q8_0)
+currpath=${PWD##*/}
+
+for quant in "${quants[@]}";
+do
+  quantize conv.bin ${currpath::-5}.$quant.gguf $quant
+done 

llama-3-cat-8b-instruct-v1.F16.gguf

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llama-3-cat-8b-instruct-v1.Q5_K_S.gguf

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