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Introducing `lms` - LM Studio's companion cli tool May 2, 2024 By LM Studio Team Today, alongside LM Studio 0.2.22, we're releasing the first version of lms — LM Studio's companion cli tool. With lms you can load/unload models, start/stop the API server, and inspect raw LLM input (not just output). It's developed on github and we're welcoming issues and PRs from the community. lms ships with LM Studio and lives in LM Studio's working directory, under ~/.cache/lm-studio/bin/. When you update LM Studio, it also updates your lms version. If you're a developer, you can also build lms from source. Bootstrap lms on your system​ You need to run LM Studio at least once before you can use lms. Afterwards, open your terminal and run one of these commands, depending on your operating system: # Mac / Linux: ~/.cache/lm-studio/bin/lms bootstrap # Windows: cmd /c %USERPROFILE%/.cache/lm-studio/bin/lms.exe bootstrap Afterwards, open a new terminal window and run lms. This is the current output you will get: $ lms __ __ ___ ______ ___ _______ ____ / / / |/ / / __/ /___ _____/ (_)__ / ___/ / / _/ / /__/ /|_/ / _\ \/ __/ // / _ / / _ \ / /__/ /___/ / /____/_/ /_/ /___/\__/\_,_/\_,_/_/\___/ \___/____/___/ lms - LM Studio CLI - v0.2.22 GitHub: https://github.com/lmstudio-ai/lmstudio-cli Usage lms <subcommand> where <subcommand> can be one of: - status - Prints the status of LM Studio - server - Commands for managing the local server - ls - List all downloaded models - ps - List all loaded models - load - Load a model - unload - Unload a model - create - Create a new project with scaffolding - log - Log operations. Currently only supports streaming logs from LM Studio via `lms log stream` - version - Prints the version of the CLI - bootstrap - Bootstrap the CLI For more help, try running `lms <subcommand> --help` lms is MIT Licensed and it is developed in this repository on GitHub: https://github.com/lmstudio-ai/lms Use lms to automate and debug your workflows​ Start and stop the local server​ lms server start lms server stop List the local models on the machine​ lms ls This will reflect the current LM Studio models directory, which you set in 📂 My Models tab in the app. List the currently loaded models​ lms ps Load a model (with options)​ lms load [--gpu=max|auto|0.0-1.0] [--context-length=1-N] --gpu=1.0 means 'attempt to offload 100% of the computation to the GPU'. Optionally, assign an identifier to your local LLM: lms load TheBloke/phi-2-GGUF --identifier="gpt-4-turbo" This is useful if you want to keep the model identifier consistent. Unload models​ lms unload [--all] Debug your prompting with lms log stream​ lms log stream allows you to inspect the exact input string that goes to the model. This is particularly useful for debugging prompt template issues and other unexpected LLM behaviors. $ lms log stream I Streaming logs from LM Studio timestamp: 5/2/2024, 9:49:47 PM type: llm.prediction.input modelIdentifier: TheBloke/TinyLlama-1.1B-1T-OpenOrca-GGUF/tinyllama-1.1b-1t-openorca.Q2_K.gguf modelPath: TheBloke/TinyLlama-1.1B-1T-OpenOrca-GGUF/tinyllama-1.1b-1t-openorca.Q2_K.gguf input: "Below is an instruction that describes a task. Write a response that appropriately completes the request. ### Instruction: Hello, what's your name? ### Response: " lmstudio.js​ lms uses lmstudio.js to interact with LM Studio. You can build your own programs that can do what lms does and much more. lmstudio.js is in pre-release public alpha. Follow along on GitHub: https://github.com/lmstudio-ai/lmstudio.js. Discuss all things lms and lmstudio.js in the new #dev-chat channel on the LM Studio Discord Server. Download LM Studio for Mac / Windows / Linux from https://lmstudio.ai. LM Studio 0.2.22 AMD ROCm - Technology Preview is available in https://lmstudio.ai/rocm LM Studio on Twitter: https://twitter.com/LMStudioAI Older Post Use Llama 3 in LM Studio Docs Docs Community Discord Twitter More Download LM Studio Copyright © 2024 LM Studio

DraftMost Drafts’ Shortcut actions return a Draft object, or in the case of query actions, arrays of Draft objects. Each of these objects contains the the following values about the draft:**Draft**: The primary identifier for the draft. This can be used in subsequent Shortcut actions to identify the draft.**UUID** *string*: The UUID of the draft.**Content** *string*: The full text of the draft.**Link** *string*: A permalink to the draft, using the drafts://open URL action.**Title** *string*: The first line of the draft.**Tags** *array of strings*: Tags assigned to the draft.**Flagged** *boolean*: Flagged status of the draft.**Folder**: Folder the draft is currently located in. Possible values: Inbox, Archive or Trash.**Syntax Definition**: Syntax highlighting mode assigned to the draft.**Creation Date** *date*: Timestamp of draft creation.**Creation Location** *location*: Location the draft was created.**Modification Date** *date*: Timestamp of draft’s last modification.**Modification Location** *location*: Location the draft was last modified.Workspace**Workspace**: The primary identifier for the workspace. This can be used in subsequent Shortcut actions to identify the workspace.**Name**: The name assigned to the workspace.⠀Action**Action**: The primary identifier for the action. This can be used in subsequent Shortcut actions to identify the action.**Name**: The name assigned to the action.

Colaboratory Frequently Asked Questions The Basics What is Colaboratory?link Colab is a hosted Jupyter Notebook service that requires no setup to use and provides free of charge access to computing resources, including GPUs and TPUs. Colab is especially well suited to machine learning, data science, and education. Is it really free of charge to use?link Yes. Colab is free of charge to use. Seems too good to be true. What are the limitations?link In order to provide access to as many students and under-resourced groups around the world as possible, Colab prioritizes users who are actively programming in a notebook. Colab also restricts actions that negatively impact others or are associated with bypassing our anti-abuse policies. See Which activities are restricted in Colab? for a list of actions that are disallowed. Colab resources are not guaranteed and not unlimited, and usage limits sometimes fluctuate. This is necessary for Colab to be able to provide resources free of charge. For more details, see Resource Limits. Which activities are restricted in Colab?link Colab managed runtimes prohibit abusive actions that negatively impact others and actions associated with bypassing our policies. The following are disallowed from all managed Colab runtimes: file hosting, media serving, or other web service offerings not related to interactive compute with Colab downloading torrents or engaging in peer-to-peer file-sharing connecting to remote proxies mining cryptocurrency running denial-of-service attacks password cracking using multiple accounts to work around access or resource usage restrictions creating deepfakes Unfortunately it is not possible to provide more specificity in how our abuse detection system works as bad actors try to take advantage of the compute subsidies Colab offers. In addition to these restrictions, and in order to provide access to students and under-resourced groups around the world, Colab prioritizes users who are actively programming in a notebook. The following are disallowed from managed Colab runtimes running free of charge, without a positive Colab compute unit balance, and may be terminated at any time without warning: remote control such as SSH shells, remote desktops bypassing the notebook UI to interact primarily via a web UI chess training running distributed computing workers You can remove these types of restrictions by purchasing one of our paid plans here and maintaining a positive compute unit balance. You may find not all runtimes that match the descriptions are terminated; we attempt to support as much as we can within reason to benefit the global community. You can purchase guaranteed resources without Colab-enforced usage limitations via GCP Marketplace or Colab Enterprise or use your own compute via a local runtime you control. Note that Google Drive mounting on the runtime filesystem will not work with these approaches. Why does my Colab runtime keep terminating prematurely?link In order to provide access to students and under-resourced groups around the world, Colab prioritizes users who are actively programming in a notebook. Users in our free of charge tier commonly experience runtime terminations when attempting to bypass the notebook UI and using a web UI on a Colab managed runtime for content generation. These experiences are popular and impressive, but are compute intensive and fall outside our priorities for our free of charge tier users, who we want to help in programming. You can remove these types of restrictions by purchasing one of our paid plans here. You can purchase guaranteed resources without Colab-enforced usage limitations via GCP Marketplace or Colab Enterprise or use your own compute via a local runtime you control. Note that Google Drive mounting on the runtime filesystem will not work with these approaches. What is the difference between Jupyter and Colab?link Jupyter is the open source project on which Colab is based. Colab allows you to use and share Jupyter notebooks with others without having to download, install, or run anything. Using Colab Where are my notebooks stored, and can I share them?link Colab notebooks are stored in Google Drive, or can be loaded from GitHub. Colab notebooks can be shared just as you would with Google Docs or Sheets. Simply click the Share button at the top right of any Colab notebook, or follow these Google Drive file sharing instructions. If I share my notebook, what will be shared?link If you choose to share a notebook, the full contents of your notebook (text, code, output, and comments) will be shared. You can omit code cell output from being saved or shared by using Edit > Notebook settings > Omit code cell output when saving this notebook. The virtual machine you’re using, including any custom files and libraries that you’ve setup, will not be shared. So it’s a good idea to include cells which install and load any custom libraries or files that your notebook needs. Can I impor