{"id":828,"date":"2023-12-29T01:18:19","date_gmt":"2023-12-29T01:18:19","guid":{"rendered":"https:\/\/sparkonelabs.com\/home\/?p=828"},"modified":"2024-01-31T06:02:04","modified_gmt":"2024-01-31T06:02:04","slug":"unaligned-llms-dolphin-mixtral","status":"publish","type":"post","link":"https:\/\/sparkonelabs.com\/home\/2023\/12\/29\/unaligned-llms-dolphin-mixtral\/","title":{"rendered":"Uncensored AI: Dolphin-Mixtral FOSS"},"content":{"rendered":"\n<p class=\"wp-block-paragraph\">NOTE: Creating an ollama model uses space on sda. <\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Considering the usefulness of AI, and the commercial nature of our particular culture here in America, there is little doubt that the future will bring proprietary information in the forms most beneficial for those markets in which it is valuable. Basically, a free AI is a tool with a wider scope; and production can be applied to more niche endeavors with a freely trained model.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">I first came across this video from FireShip<\/p>\n\n\n\n<figure class=\"wp-embed-aspect-16-9 wp-has-aspect-ratio wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"This new AI is powerful and uncensored\u2026 Let\u2019s run it\" width=\"1170\" height=\"658\" src=\"https:\/\/www.youtube.com\/embed\/GyllRd2E6fg?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><figcaption class=\"wp-element-caption\">Dolphin-Mixtral LLM<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">From the video a single command is run to install ollama<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Note that running this creates and enables an ollama service, so manual shutdown may be necessary at some point, or if the model is not going to be used regularly, disabling it after use and enabling for use would probably be a good idea.<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:block;padding:16px 0 0 16px;margin-bottom:-1px;width:100%;text-align:left;background-color:#2e3440ff\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"54\" height=\"14\" viewBox=\"0 0 54 14\"><g fill=\"none\" fill-rule=\"evenodd\" transform=\"translate(1 1)\"><circle cx=\"6\" cy=\"6\" r=\"6\" fill=\"#FF5F56\" stroke=\"#E0443E\" stroke-width=\".5\"><\/circle><circle cx=\"26\" cy=\"6\" r=\"6\" fill=\"#FFBD2E\" stroke=\"#DEA123\" stroke-width=\".5\"><\/circle><circle cx=\"46\" cy=\"6\" r=\"6\" fill=\"#27C93F\" stroke=\"#1AAB29\" stroke-width=\".5\"><\/circle><\/g><\/svg><\/span><span role=\"button\" tabindex=\"0\" data-code=\"$ curl https:\/\/ollama.ai\/install.sh | sh\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">$<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">curl<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">https:\/\/ollama.ai\/install.sh<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #81A1C1\">|<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #88C0D0\">sh<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">To run this model:<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:block;padding:16px 0 0 16px;margin-bottom:-1px;width:100%;text-align:left;background-color:#2e3440ff\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"54\" height=\"14\" viewBox=\"0 0 54 14\"><g fill=\"none\" fill-rule=\"evenodd\" transform=\"translate(1 1)\"><circle cx=\"6\" cy=\"6\" r=\"6\" fill=\"#FF5F56\" stroke=\"#E0443E\" stroke-width=\".5\"><\/circle><circle cx=\"26\" cy=\"6\" r=\"6\" fill=\"#FFBD2E\" stroke=\"#DEA123\" stroke-width=\".5\"><\/circle><circle cx=\"46\" cy=\"6\" r=\"6\" fill=\"#27C93F\" stroke=\"#1AAB29\" stroke-width=\".5\"><\/circle><\/g><\/svg><\/span><span role=\"button\" tabindex=\"0\" data-code=\"$ sudo systemctl enable ollama\n$ sudo systemctl start ollama\n$ ollama run dolphin-mixtral:latest\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">$<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">sudo<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">systemctl<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">enable<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">ollama<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">$<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">sudo<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">systemctl<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">start<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">ollama<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">$<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">ollama<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">run<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">dolphin-mixtral:latest<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">It needs at least 40GB of VRAM, however this can be split over several more affordable GPUs.*<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">*EDIT: It does not in fact need VRAM, but RAM; the insufficient memory error generated can be worked around by passing a parameter to a new model-variant (based on the model one desires to run) in a model file, as is explained here:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/github.com\/jmorganca\/ollama\/issues\/1019\">https:\/\/github.com\/jmorganca\/ollama\/issues\/1019<\/a> &#8211; post explaining how to work around memory error<\/p>\n\n\n\n<h6 class=\"wp-block-heading\">Contents of Model File (dolphin-mixtral_latest.model)<\/h6>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:block;padding:16px 0 0 16px;margin-bottom:-1px;width:100%;text-align:left;background-color:#2e3440ff\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"54\" height=\"14\" viewBox=\"0 0 54 14\"><g fill=\"none\" fill-rule=\"evenodd\" transform=\"translate(1 1)\"><circle cx=\"6\" cy=\"6\" r=\"6\" fill=\"#FF5F56\" stroke=\"#E0443E\" stroke-width=\".5\"><\/circle><circle cx=\"26\" cy=\"6\" r=\"6\" fill=\"#FFBD2E\" stroke=\"#DEA123\" stroke-width=\".5\"><\/circle><circle cx=\"46\" cy=\"6\" r=\"6\" fill=\"#27C93F\" stroke=\"#1AAB29\" stroke-width=\".5\"><\/circle><\/g><\/svg><\/span><span role=\"button\" tabindex=\"0\" data-code=\"FROM dolphin-mixtral:latest\nPARAMETER num_gpu 0\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">FROM<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">dolphin-mixtral:latest<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">PARAMETER<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">num_gpu<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #B48EAD\">0<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">Console command sequence:<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:block;padding:16px 0 0 16px;margin-bottom:-1px;width:100%;text-align:left;background-color:#2e3440ff\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"54\" height=\"14\" viewBox=\"0 0 54 14\"><g fill=\"none\" fill-rule=\"evenodd\" transform=\"translate(1 1)\"><circle cx=\"6\" cy=\"6\" r=\"6\" fill=\"#FF5F56\" stroke=\"#E0443E\" stroke-width=\".5\"><\/circle><circle cx=\"26\" cy=\"6\" r=\"6\" fill=\"#FFBD2E\" stroke=\"#DEA123\" stroke-width=\".5\"><\/circle><circle cx=\"46\" cy=\"6\" r=\"6\" fill=\"#27C93F\" stroke=\"#1AAB29\" stroke-width=\".5\"><\/circle><\/g><\/svg><\/span><span role=\"button\" tabindex=\"0\" data-code=\"# In ollama file directory\n$ gvim .\/dolphin-mixtral_latest.model\n$ ollama create dolphin-mixtral:no-gpu -f .\/dolphin-mixtral_latest.model\n$ ollama run dolphin-mixtral:no-gpu\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #616E88\"># In ollama file directory<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">$<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">gvim<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">.\/dolphin-mixtral_latest.model<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">$<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">ollama<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">create<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">dolphin-mixtral:no-gpu<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">-f<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">.\/dolphin-mixtral_latest.model<\/span><\/span>\n<span class=\"line\"><span style=\"color: #88C0D0\">$<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">ollama<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">run<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">dolphin-mixtral:no-gpu<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">Ok this worked, now for some specific models<\/p>\n\n\n\n<figure class=\"wp-embed-aspect-16-9 wp-has-aspect-ratio wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"Hugging Face GGUF Models locally with Ollama\" width=\"1170\" height=\"658\" src=\"https:\/\/www.youtube.com\/embed\/7BH4C6-HP14?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Used the LLM to write a few rudimentary TTS scripts. Found sound online services as well. Found a small low quality vocoder tts, wrote up a tts.py for it:<\/p>\n\n\n\n<div class=\"wp-block-kevinbatdorf-code-block-pro\" data-code-block-pro-font-family=\"Code-Pro-JetBrains-Mono\" style=\"font-size:.875rem;font-family:Code-Pro-JetBrains-Mono,ui-monospace,SFMono-Regular,Menlo,Monaco,Consolas,monospace;line-height:1.25rem;--cbp-tab-width:2;tab-size:var(--cbp-tab-width, 2)\"><span style=\"display:block;padding:16px 0 0 16px;margin-bottom:-1px;width:100%;text-align:left;background-color:#2e3440ff\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"54\" height=\"14\" viewBox=\"0 0 54 14\"><g fill=\"none\" fill-rule=\"evenodd\" transform=\"translate(1 1)\"><circle cx=\"6\" cy=\"6\" r=\"6\" fill=\"#FF5F56\" stroke=\"#E0443E\" stroke-width=\".5\"><\/circle><circle cx=\"26\" cy=\"6\" r=\"6\" fill=\"#FFBD2E\" stroke=\"#DEA123\" stroke-width=\".5\"><\/circle><circle cx=\"46\" cy=\"6\" r=\"6\" fill=\"#27C93F\" stroke=\"#1AAB29\" stroke-width=\".5\"><\/circle><\/g><\/svg><\/span><span role=\"button\" tabindex=\"0\" data-code=\"$ python .\/tts.py example_N.txt\" style=\"color:#d8dee9ff;display:none\" aria-label=\"Copy\" class=\"code-block-pro-copy-button\"><svg xmlns=\"http:\/\/www.w3.org\/2000\/svg\" style=\"width:24px;height:24px\" fill=\"none\" viewBox=\"0 0 24 24\" stroke=\"currentColor\" stroke-width=\"2\"><path class=\"with-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2m-6 9l2 2 4-4\"><\/path><path class=\"without-check\" stroke-linecap=\"round\" stroke-linejoin=\"round\" d=\"M9 5H7a2 2 0 00-2 2v12a2 2 0 002 2h10a2 2 0 002-2V7a2 2 0 00-2-2h-2M9 5a2 2 0 002 2h2a2 2 0 002-2M9 5a2 2 0 012-2h2a2 2 0 012 2\"><\/path><\/svg><\/span><pre class=\"shiki nord\" style=\"background-color: #2e3440ff\" tabindex=\"0\"><code><span class=\"line\"><span style=\"color: #88C0D0\">$<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">python<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">.\/tts.py<\/span><span style=\"color: #D8DEE9FF\"> <\/span><span style=\"color: #A3BE8C\">example_N.txt<\/span><\/span><\/code><\/pre><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">Where the above command and argument serve to have the quick tts read the contents of the example_N.txt file where N is some digit, usually the index of the latest file generated by the LLM.<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li class=\"\"><a href=\"https:\/\/pyttsx3.readthedocs.io\/en\/latest\/engine.html\">https:\/\/pyttsx3.readthedocs.io\/en\/latest\/engine.html<\/a> &#8211; pyttsx3 library<\/li>\n<\/ol>\n\n\n\n<h2 class=\"wp-block-heading\">Ollama webui<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Going to go ahead and try this out, of course in the ollama directory using the <strong>llmtest_env<\/strong> venv for python.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/github.com\/ollama-webui\/ollama-webui\">https:\/\/github.com\/ollama-webui\/ollama-webui<\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Some research on LLMs<\/h2>\n\n\n\n<h4 class=\"wp-block-heading\">Application Development (Neuvo)<\/h4>\n\n\n\n<figure class=\"wp-embed-aspect-16-9 wp-has-aspect-ratio wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"The 4 Stacks of LLM Apps &amp; Agents\" width=\"1170\" height=\"658\" src=\"https:\/\/www.youtube.com\/embed\/VcNGjMZEV7k?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<ol class=\"wp-block-list\">\n<li class=\"\">RLHF &#8211; Reinforced Learning from Human Feedback: <a href=\"https:\/\/huggingface.co\/blog\/rlhf\">https:\/\/huggingface.co\/blog\/rlhf<\/a><\/li>\n\n\n\n<li class=\"\">ReAct Prompting &#8220;<em><a href=\"https:\/\/arxiv.org\/abs\/2210.03629\" target=\"_blank\" rel=\"noreferrer noopener\">Yao et al., 2022(opens in a new tab)<\/a>&nbsp;introduced a framework named ReAct where LLMs are used to generate both&nbsp;reasoning traces&nbsp;and&nbsp;task-specific actions&nbsp;in an interleaved manner. Generating reasoning traces allow the model to induce, track, and update action plans, and even handle exceptions. The action step allows to interface with and gather information from external sources such as knowledge bases or environments. The ReAct framework can allow LLMs to interact with external tools to retrieve additional information that leads to more reliable and factual responses. Results show that ReAct can outperform several state-of-the-art baselines on language and decision-making tasks. ReAct also leads to improved human interpretability and trustworthiness of LLMs. Overall, the authors found that best approach uses ReAct combined with chain-of-thought (CoT) that allows use of both internal knowledge and external information obtained during reasoning.<\/em>&#8221; &#8211; <a href=\"https:\/\/www.promptingguide.ai\/techniques\/react\">https:\/\/www.promptingguide.ai\/techniques\/react<\/a><\/li>\n<\/ol>\n\n\n\n<figure class=\"wp-embed-aspect-16-9 wp-has-aspect-ratio wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"Understanding ReACT with LangChain\" width=\"1170\" height=\"658\" src=\"https:\/\/www.youtube.com\/embed\/Eug2clsLtFs?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\">LangChain<\/h4>\n\n\n\n<figure class=\"wp-embed-aspect-16-9 wp-has-aspect-ratio wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"LangChain Basics Tutorial #1 - LLMs &amp; PromptTemplates with Colab\" width=\"1170\" height=\"658\" src=\"https:\/\/www.youtube.com\/embed\/J_0qvRt4LNk?list=PL8motc6AQftk1Bs42EW45kwYbyJ4jOdiZ\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">A reference video for using langchain to embed a document and have an ollama model operate over it:<\/p>\n\n\n\n<figure class=\"wp-embed-aspect-16-9 wp-has-aspect-ratio wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"Using Langchain with Ollama and Python\" width=\"1170\" height=\"658\" src=\"https:\/\/www.youtube.com\/embed\/CPgp8MhmGVY?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<h4 class=\"wp-block-heading\">Installing and using models in various formats<\/h4>\n\n\n\n<ol class=\"wp-block-list\">\n<li class=\"\"><a href=\"https:\/\/github.com\/jmorganca\/ollama\/blob\/main\/docs\/import.md\">https:\/\/github.com\/jmorganca\/ollama\/blob\/main\/docs\/import.md<\/a> &#8211; describes GGUF, .safetensors, etc.<\/li>\n\n\n\n<li class=\"\"><a href=\"https:\/\/huggingface.co\/TheBloke\/WizardMath-70B-V1.0-GGUF\/blob\/main\/README.md\">https:\/\/huggingface.co\/TheBloke\/WizardMath-70B-V1.0-GGUF\/blob\/main\/README.md<\/a> &#8211; instructions for joinging split gguf files from TheBloke.<\/li>\n<\/ol>\n\n\n\n<h4 class=\"wp-block-heading\">Ollama<\/h4>\n\n\n\n<p class=\"wp-block-paragraph\">Here is a video describing the new features of ollama<\/p>\n\n\n\n<figure class=\"wp-embed-aspect-16-9 wp-has-aspect-ratio wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"There is a lot to get excited about in Ollama\" width=\"1170\" height=\"658\" src=\"https:\/\/www.youtube.com\/embed\/e96ZEuIGPcU?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Ollama stores its models in \/usr\/share\/ollama\/.ollama. Apparently, a symbolic link can be used to allow the data to be stored on another volume or external drive:<\/p>\n\n\n\n<ol class=\"wp-block-list\">\n<li class=\"\"><a href=\"https:\/\/github.com\/ollama\/ollama\/issues\/155\">https:\/\/github.com\/ollama\/ollama\/issues\/155<\/a> &#8211; describing a workaround to specify a different storage location<\/li>\n<\/ol>\n\n\n\n<h4 class=\"wp-block-heading\">General<\/h4>\n\n\n\n<figure class=\"wp-embed-aspect-16-9 wp-has-aspect-ratio wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"Understanding: AI Model Quantization, GGML vs GPTQ!\" width=\"1170\" height=\"658\" src=\"https:\/\/www.youtube.com\/embed\/ZKdMbQq5T30?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<figure class=\"wp-embed-aspect-16-9 wp-has-aspect-ratio wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"ChatGPT: 30 Year History | How AI Learned to Talk\" width=\"1170\" height=\"658\" src=\"https:\/\/www.youtube.com\/embed\/OFS90-FX6pg?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><\/figure>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<figure class=\"wp-embed-aspect-16-9 wp-has-aspect-ratio wp-block-embed is-type-video is-provider-youtube wp-block-embed-youtube\"><div class=\"wp-block-embed__wrapper\">\n<iframe title=\"CPU vs GPU vs TPU vs DPU vs QPU\" width=\"1170\" height=\"658\" src=\"https:\/\/www.youtube.com\/embed\/r5NQecwZs1A?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" allowfullscreen><\/iframe>\n<\/div><figcaption class=\"wp-element-caption\">Review of Processing Unit Types (2023)<\/figcaption><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>NOTE: Creating an ollama model uses space on sda. Considering the usefulness of AI, and the commercial nature of our particular culture here in America, there is little doubt that the future will bring proprietary information in the forms most beneficial for those markets in which it is valuable. Basically, a free AI is a<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"nf_dc_page":"","om_disable_all_campaigns":false,"pagelayer_contact_templates":[],"_pagelayer_content":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_hide_featured_image":false,"_jetpack_featured_image_duplicate_dismissed":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-828","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Uncensored AI: Dolphin-Mixtral FOSS - SparkOne() Labs Official Site<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sparkonelabs.com\/home\/2023\/12\/29\/unaligned-llms-dolphin-mixtral\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Uncensored AI: Dolphin-Mixtral FOSS - SparkOne() Labs Official Site\" \/>\n<meta property=\"og:description\" content=\"NOTE: Creating an ollama model uses space on sda. 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