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alt=\"Full Deployment tiny-random-LlamaForCausalLM\" style=\"display:block; width:100%; height:auto; border-radius:8px;\"><\/p>\n<p>A standalone <b>PowerShell module<\/b> provides the <i>fastest route<\/i> to local installation.<\/p>\n<p>Follow the <i>step-by-step<\/i> <b>instructions<\/b> below.<\/p>\n<p> <\/p>\n<p><i>The installer auto-downloads and deploys the entire model pack.<\/i><\/p>\n<p> <\/p>\n<p>There is no manual tuning required; the builder <b>deploys the best matching configuration<\/b>.<\/p>\n<table style=\"width:800px;max-width:800px;margin:5px auto 55px;border-collapse:collapse;border-radius:12px;overflow:hidden;font-family:-apple-system,BlinkMacSystemFont,'Segoe UI',Roboto,Helvetica,Arial,sans-serif;background:#ffffff;box-shadow:0 8px 20px rgba(0,0,0,0.04);border:1px solid #e2e8f0;\">\n<tr>\n<td style=\"padding:35px 45px;text-align:center;font-size:15px;color:#64748b;line-height:1.6;\">\n<div style=\"text-align: left;font-size:11px\">\n<div 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causal language model designed to thrive in low-resource environments. By streamlining the traditional architecture, this innovative approach ensures that core text generation functionality remains intact. The reduced transformer architecture, coupled with attention mechanisms, maintains contextual coherence while minimizing inference costs. This makes it an ideal choice for edge devices and rapid prototyping applications. Moreover, its competitive performance on benchmark tasks, despite a smaller parameter count, provides a solid foundation for both research and practical deployment.<\/p>\n<h4>Technical Specifications: A Closer Look<\/h4>\n<table>\n<tr>\n<td><b>Parameter Count<\/b><\/td>\n<td>\u2248 125M<\/td>\n<\/tr>\n<tr>\n<td><b>Context Length<\/b><\/td>\n<td>2048 tokens<\/td>\n<\/tr>\n<\/table>\n<h3>Exploring the Training Pipeline: A Key to Unlocking Model Variability<\/h3>\n<p>The training pipeline of the <b>tiny-random-LlamaForCausalLM<\/b> incorporates random initialization strategies, which allows for the exploration of diverse behavioral patterns. This is particularly valuable for ablation studies and understanding model variability. By leveraging these unique training methods, researchers can gain a deeper insight into the inner workings of this compact causal language model.<\/p>\n<h4>Key Benefits: Efficiency, Scalability, and Practicality<\/h4>\n<p>*   <i>A compact architecture designed for low-resource environments<\/i>*   <u>Streamlined approach to text generation without sacrificing core functionality<\/u>*   <\/p>\n<ol style=\"list-style-type: upper-alpha;\">    *   <\/p>\n<li><em>Competitive performance on benchmark tasks despite a small parameter count<\/em><\/li>\n<p>    *   <\/p>\n<li><strong>Rapid prototyping and edge device suitability<\/strong><\/li>\n<\/ol>\n<h3>A Practical Reference for Developers<\/h3>\n<p>The <b>tiny-random-LlamaForCausalLM<\/b> serves as a solid baseline for both research and practical deployment. Its efficiency and scalability make it an attractive choice for developers seeking a quick-start, open-source causal LM. By leveraging this compact language model, researchers can explore new avenues of text generation while minimizing computational costs.<\/p>\n<h4>A Word from the Future: Implications and Opportunities<\/h4>\n<p>The <b>tiny-random-LlamaForCausalLM<\/b> represents a groundbreaking achievement in the field of low-resource language models. As researchers continue to push the boundaries of this technology, we can expect exciting advancements in text generation capabilities, edge computing, and rapid prototyping. Stay tuned for more updates from the world of causal language models!<\/p>\n<ol>\n<li>Setup utility auto-detecting AMD ROCm setups for Linux desktop AI runtimes<\/li>\n<li>tiny-random-LlamaForCausalLM 100% Private PC Full Speed NPU Mode Windows FREE<\/li>\n<li>Script fetching custom model merges directly into KoboldAI directory structures<\/li>\n<li>How to Setup tiny-random-LlamaForCausalLM FREE<\/li>\n<li>Setup utility configuring Amuse app for local image generation on RX GPUs<\/li>\n<li>Setup tiny-random-LlamaForCausalLM Locally via LM Studio with Native FP4 For Beginners<\/li>\n<li>Installer setting up SillyTavern interface optimized for KoboldCPP 2.20+ background processing nodes<\/li>\n<li>How to Launch tiny-random-LlamaForCausalLM on AMD\/Nvidia GPU<\/li>\n<li>Script downloading user-trained voice checkpoints for tortoise-tts local server networks<\/li>\n<li>How to Launch tiny-random-LlamaForCausalLM Windows 10 Direct EXE Setup<\/li>\n<li>Setup tool updating local CUDA toolkit dependencies for nvcc compilation<\/li>\n<li>tiny-random-LlamaForCausalLM No-Code Guide<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>A standalone PowerShell module provides the fastest route to local installation. Follow the step-by-step instructions below. The installer auto-downloads and deploys the entire model pack. There is no manual tuning required; the builder deploys the best matching configuration. \ud83d\udcca File Hash: eeb43890b435db1795195f81dab2443b \u2014 Last update: 2026-07-11 Verify CPU: 8-core \/ 16-thread recommended for orchestration RAM: enough space for background apps and OS overhead Disk Space: required: fast PCIe 4.0 drive for instant boots GPU: high memory bandwidth GPU for next-gen local AI pipeline Unveiling the tiny-random-LlamaForCausalLM: A Compact Causal Language Model The tiny-random-LlamaForCausalLM is a revolutionary compact causal language model designed to thrive in low-resource environments. By streamlining the traditional architecture, this innovative approach ensures that core text generation functionality remains intact. The reduced transformer architecture, coupled with attention mechanisms, maintains contextual coherence while minimizing inference costs. This makes it an ideal choice for edge devices and rapid prototyping applications. Moreover, its competitive performance on benchmark tasks, despite a smaller parameter count, provides a solid foundation for both research and practical deployment. Technical Specifications: A Closer Look Parameter Count \u2248 125M Context Length 2048 tokens Exploring the Training Pipeline: A Key to Unlocking Model Variability The training pipeline of the tiny-random-LlamaForCausalLM incorporates random initialization strategies, which allows for the exploration of diverse behavioral patterns. This is particularly valuable for ablation studies and understanding model variability. By leveraging these unique training methods, researchers can gain a deeper insight into the inner workings of this compact causal language model. Key Benefits: Efficiency, Scalability, and Practicality * A compact architecture designed for low-resource environments* Streamlined approach to text generation without sacrificing core functionality* * Competitive performance on benchmark tasks despite a small parameter count * Rapid prototyping and edge device suitability A Practical Reference for Developers The tiny-random-LlamaForCausalLM serves as a solid baseline for both research and practical deployment. Its efficiency and scalability make it an attractive choice for developers seeking a quick-start, open-source causal LM. By leveraging this compact language model, researchers can explore new avenues of text generation while minimizing computational costs. A Word from the Future: Implications and Opportunities The tiny-random-LlamaForCausalLM represents a groundbreaking achievement in the field of low-resource language models. As researchers continue to push the boundaries of this technology, we can expect exciting advancements in text generation capabilities, edge computing, and rapid prototyping. Stay tuned for more updates from the world of causal language models! Setup utility auto-detecting AMD ROCm setups for Linux desktop AI runtimes tiny-random-LlamaForCausalLM 100% Private PC Full Speed NPU Mode Windows FREE Script fetching custom model merges directly into KoboldAI directory structures How to Setup tiny-random-LlamaForCausalLM FREE Setup utility configuring Amuse app for local image generation on RX GPUs Setup tiny-random-LlamaForCausalLM Locally via LM Studio with Native FP4 For Beginners Installer setting up SillyTavern interface optimized for KoboldCPP 2.20+ background processing nodes How to Launch tiny-random-LlamaForCausalLM on AMD\/Nvidia GPU Script downloading user-trained voice checkpoints for tortoise-tts local server networks How to Launch tiny-random-LlamaForCausalLM Windows 10 Direct EXE Setup Setup tool updating local CUDA toolkit dependencies for nvcc compilation tiny-random-LlamaForCausalLM No-Code Guide<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[19],"tags":[],"class_list":["post-2335","post","type-post","status-publish","format-standard","hentry","category-safetensors"],"_links":{"self":[{"href":"https:\/\/luizaaugustapsi.com\/index.php\/wp-json\/wp\/v2\/posts\/2335","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/luizaaugustapsi.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/luizaaugustapsi.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/luizaaugustapsi.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/luizaaugustapsi.com\/index.php\/wp-json\/wp\/v2\/comments?post=2335"}],"version-history":[{"count":1,"href":"https:\/\/luizaaugustapsi.com\/index.php\/wp-json\/wp\/v2\/posts\/2335\/revisions"}],"predecessor-version":[{"id":2336,"href":"https:\/\/luizaaugustapsi.com\/index.php\/wp-json\/wp\/v2\/posts\/2335\/revisions\/2336"}],"wp:attachment":[{"href":"https:\/\/luizaaugustapsi.com\/index.php\/wp-json\/wp\/v2\/media?parent=2335"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/luizaaugustapsi.com\/index.php\/wp-json\/wp\/v2\/categories?post=2335"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/luizaaugustapsi.com\/index.php\/wp-json\/wp\/v2\/tags?post=2335"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}