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alt=\"Quick Run tiny-random-LlamaForCausalLM\" style=\"display:block; width:100%; height:auto; border-radius:8px;\"><\/p>\n<p>To get this model running locally in <i>no time<\/i>, utilize the built-in <b>WSL tools<\/b>.<\/p>\n<p>Follow the <i>straightforward<\/i> <b>walkthrough<\/b> provided below.<\/p>\n<p> <\/p>\n<p><i>The loader auto-caches the model archive (several GBs included).<\/i><\/p>\n<p> <\/p>\n<p>You don&#8217;t need to tweak anything; the installer <b>picks the highest performing setup<\/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, offering a streamlined approach to text generation without compromising core functionality. Leveraging a reduced transformer architecture with attention mechanisms ensures contextual coherence while maintaining minimal inference costs, making it suitable for edge devices and rapid prototyping. This innovative approach has enabled the model to achieve competitive performance on benchmark tasks despite its small parameter count, providing a solid baseline for both research and practical deployment. The training pipeline incorporates random initialization strategies to explore diverse behavioral patterns, which is invaluable for ablation studies and understanding model variability. Furthermore, this approach allows for efficient exploration of new parameters, enabling rapid prototyping and development. By doing so, the <b>tiny-random-LlamaForCausalLM<\/b> has become an attractive option for developers seeking a quick-start, open-source causal LM.<\/p>\n<ul style=\"list-style-type: none;\">\n<li>One of the key advantages of the <b>tiny-random-LlamaForCausalLM<\/b> is its reduced parameter count, which makes it more efficient and scalable. With approximately 125 million parameters, this model is well-suited for deployment on edge devices.<\/li>\n<li>The model&#8217;s context length is also noteworthy, with a maximum of 2048 tokens. This allows for more comprehensive understanding of complex sentences and paragraphs.<\/li>\n<li>Another significant aspect of the <b>tiny-random-LlamaForCausalLM<\/b> is its ability to balance efficiency and capability. By leveraging attention mechanisms and random initialization strategies, this model has been able to achieve competitive performance on benchmark tasks while maintaining minimal inference costs.<\/li>\n<\/ul>\n<table style=\"border-collapse: collapse;\">\n<tr>\n<th>\n<h4>Key Features<\/h4>\n<\/th>\n<td>\u2248 125M<\/td>\n<\/tr>\n<tr>\n<th>\n<h4>Context Length<\/h4>\n<\/th>\n<td>2048 tokens<\/td>\n<\/tr>\n<\/table>\n<h3>Technical Specifications: A Closer Look<\/h3>\n<ol style=\"list-style-type: decimal;\">\n<li>The model&#8217;s architecture is based on a reduced transformer architecture, which allows for more efficient inference and better handling of low-resource environments.<\/li>\n<li>The attention mechanisms used in this model enable contextual coherence while maintaining minimal inference costs, making it suitable for edge devices and rapid prototyping.<\/li>\n<li>The training pipeline incorporates random initialization strategies to explore diverse behavioral patterns, enabling ablation studies and understanding model variability.<\/li>\n<\/ol>\n<h4>Why Choose the tiny-random-LlamaForCausalLM?<\/h4>\n<p>The <b>tiny-random-LlamaForCausalLM<\/b> offers a streamlined approach to text generation without sacrificing core functionality. By leveraging a reduced transformer architecture with attention mechanisms, this model has been able to achieve competitive performance on benchmark tasks despite its small parameter count. Its training pipeline incorporates random initialization strategies, enabling efficient exploration of new parameters and rapid prototyping. With its compact design, the <b>tiny-random-LlamaForCausalLM<\/b> is an attractive option for developers seeking a quick-start, open-source causal LM.<\/p>\n<h4>A Solid Baseline for Research and Deployment<\/h4>\n<p>The <b>tiny-random-LlamaForCausalLM<\/b> has become a solid baseline for both research and practical deployment. Its competitive performance on benchmark tasks, combined with its efficiency and scalability, make it an attractive option for developers seeking a quick-start, open-source causal LM. By leveraging the attention mechanisms and random initialization strategies, this model is well-suited for edge devices and rapid prototyping, enabling efficient exploration of new parameters and rapid development.<\/p>\n<p style=\"text-align: center;\">Overall, the <b>tiny-random-LlamaForCausalLM<\/b> balances efficiency and capability, serving as a practical reference for developers seeking a quick-start, open-source causal LM.<\/p>\n<ol>\n<li>Setup utility integrating local LLM endpoints into LibreChat frontend<\/li>\n<li>tiny-random-LlamaForCausalLM via WebGPU (Browser) No Admin Rights Dummy Proof Guide<\/li>\n<li>Script downloading custom LoRA modules for advanced SDXL photorealism<\/li>\n<li>Deploy tiny-random-LlamaForCausalLM on AMD\/Nvidia GPU Quantized GGUF 2026\/2027 Tutorial<\/li>\n<li>Installer configuring multi-GPU tensor parallelism for large models<\/li>\n<li>Quick Run tiny-random-LlamaForCausalLM via WebGPU (Browser) with 1M Context FREE<\/li>\n<li>Downloader pulling optimized segmentation models for local image tasks<\/li>\n<li>Install tiny-random-LlamaForCausalLM No Admin Rights For Beginners FREE<\/li>\n<li>Installer configuring multi-user access permissions for local Ollama nodes<\/li>\n<li>Setup tiny-random-LlamaForCausalLM 100% Private PC Step-by-Step FREE<\/li>\n<\/ol>\n<p><a href='https:\/\/doneiteasy.com\/category\/keys\/'>https:\/\/doneiteasy.com\/category\/keys\/<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>To get this model running locally in no time, utilize the built-in WSL tools. Follow the straightforward walkthrough provided below. The loader auto-caches the model archive (several GBs included). You don&#8217;t need to tweak anything; the installer picks the highest performing setup. \ud83d\uddb9 HASH-SUM: e4177864ba026807aa87d356dc751cd5 | \ud83d\udcc5 Updated on: 2026-07-15 Verify CPU: multi-threading optimized for [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[145],"tags":[],"class_list":["post-3427","post","type-post","status-publish","format-standard","hentry","category-embedders"],"_links":{"self":[{"href":"https:\/\/www.nishatiassociates.co.tz\/index.php?rest_route=\/wp\/v2\/posts\/3427","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.nishatiassociates.co.tz\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.nishatiassociates.co.tz\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.nishatiassociates.co.tz\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.nishatiassociates.co.tz\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3427"}],"version-history":[{"count":1,"href":"https:\/\/www.nishatiassociates.co.tz\/index.php?rest_route=\/wp\/v2\/posts\/3427\/revisions"}],"predecessor-version":[{"id":3428,"href":"https:\/\/www.nishatiassociates.co.tz\/index.php?rest_route=\/wp\/v2\/posts\/3427\/revisions\/3428"}],"wp:attachment":[{"href":"https:\/\/www.nishatiassociates.co.tz\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3427"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.nishatiassociates.co.tz\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=3427"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.nishatiassociates.co.tz\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=3427"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}