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separatrix    
分隔号; 分界面; 分界线

分隔号; 分介面; 分界线

separatrix
n 1: a punctuation mark (/) used to separate related items of
information [synonym: {solidus}, {slash}, {virgule},
{diagonal}, {stroke}, {separatrix}]


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  • ollama - Reddit
    r ollama How good is Ollama on Windows? I have a 4070Ti 16GB card, Ryzen 5 5600X, 32GB RAM I want to run Stable Diffusion (already installed and working), Ollama with some 7B models, maybe a little heavier if possible, and Open WebUI I don't want to have to rely on WSL because it's difficult to expose that to the rest of my network I've been searching for guides, but they all seem to either
  • Local Ollama Text to Speech? : r robotics - Reddit
    Yes, I was able to run it on a RPi Ollama works great Mistral, and some of the smaller models work Llava takes a bit of time, but works For text to speech, you’ll have to run an API from eleveabs for example I haven’t found a fast text to speech, speech to text that’s fully open source yet If you find one, please keep us in the loop
  • How to manually install a model? : r ollama - Reddit
    I'm currently downloading Mixtral 8x22b via torrent Until now, I've always ran ollama run somemodel:xb (or pull) So once those >200GB of glorious…
  • HOW TO GET UNCENSORED MODELS LIKE DOLPHIN-MIXTRAL TO ACTUALLY . . . - Reddit
    Next, type this in terminal: ollama create dolph -f modelfile dolphin The dolph is the custom name of the new model You can rename this to whatever you want Once you hit enter, it will start pulling the model specified in the FROM line from ollama's library and transfer over the model layer data to the new custom model
  • Training a model with my own data : r LocalLLaMA - Reddit
    I'm using ollama to run my models I want to use the mistral model, but create a lora to act as an assistant that primarily references data I've supplied during training This data will include things like test procedures, diagnostics help, and general process flows for what to do in different scenarios
  • Best Model to locally run in a low end GPU with 4 GB RAM right now
    I am a total newbie to LLM space As the title says, I am trying to get a decent model for coding fine tuning in a lowly Nvidia 1650 card I am excited about Phi-2 but some of the posts here indicate it is slow due to some reason despite being a small model EDIT: I have 4 GB GPU RAM and in addition to that 16 Gigs of ordinary DDR3 RAM I wasn't aware these 16 Gigs + CPU could be used until it
  • Ollama not using GPUs : r ollama - Reddit
    Don't know Debian, but in arch, there are two packages, "ollama" which only runs cpu, and "ollama-cuda" Maybe the package you're using doesn't have cuda enabled, even if you have cuda installed Check if there's a ollama-cuda package If not, you might have to compile it with the cuda flags I couldn't help you with that
  • I dont get Ollama : r LocalLLaMA - Reddit
    Think of Ollama, transformers, Llama cpp, Exllama, and other names you'll come across like they're a game engine Most of the files on Huggingface just tell the engine how to produce the neural networks in the AI and contain the relationship values between the tokens
  • Why should I use Ollama when there is ChatGPT and Bard? : r ollama - Reddit
    For me Ollama provides basically three benefits: Working with sensitive data I'm working in the bank and being able to use LLM for data processing without exposing the data to any third-parties is the only way to do it Ollama (and basically any other LLM) doesn't let the data I'm processing leaving my computer Censorship





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