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Update domain name references in docs and install script (#2435)
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@ -10,7 +10,7 @@ Create new models or modify models already in the library using the Modelfile. L
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Import models using source model weights found on Hugging Face and similar sites by referring to the **[Import Documentation](./import.md)**.
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Installing on Linux in most cases is easy using the script on Ollama.ai. To get more detail about the install, including CUDA drivers, see the **[Linux Documentation](./linux.md)**.
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Installing on Linux in most cases is easy using the script on [ollama.com/download](ollama.com/download). To get more detail about the install, including CUDA drivers, see the **[Linux Documentation](./linux.md)**.
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Many of our users like the flexibility of using our official Docker Image. Learn more about using Docker with Ollama using the **[Docker Documentation](https://hub.docker.com/r/ollama/ollama)**.
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@ -123,9 +123,9 @@ ollama run example "What is your favourite condiment?"
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Publishing models is in early alpha. If you'd like to publish your model to share with others, follow these steps:
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1. Create [an account](https://ollama.ai/signup)
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1. Create [an account](https://ollama.com/signup)
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2. Run `cat ~/.ollama/id_ed25519.pub` to view your Ollama public key. Copy this to the clipboard.
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3. Add your public key to your [Ollama account](https://ollama.ai/settings/keys)
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3. Add your public key to your [Ollama account](https://ollama.com/settings/keys)
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Next, copy your model to your username's namespace:
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@ -139,7 +139,7 @@ Then push the model:
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ollama push <your username>/example
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```
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After publishing, your model will be available at `https://ollama.ai/<your username>/example`.
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After publishing, your model will be available at `https://ollama.com/<your username>/example`.
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## Quantization reference
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@ -3,9 +3,11 @@
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## Install
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Install Ollama running this one-liner:
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>
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```bash
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curl https://ollama.ai/install.sh | sh
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curl -fsSL https://ollama.com/install.sh | sh
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```
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## Manual install
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@ -15,7 +17,7 @@ curl https://ollama.ai/install.sh | sh
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Ollama is distributed as a self-contained binary. Download it to a directory in your PATH:
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```bash
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sudo curl -L https://ollama.ai/download/ollama-linux-amd64 -o /usr/bin/ollama
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sudo curl -L https://ollama.com/download/ollama-linux-amd64 -o /usr/bin/ollama
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sudo chmod +x /usr/bin/ollama
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```
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@ -75,13 +77,13 @@ sudo systemctl start ollama
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Update ollama by running the install script again:
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```bash
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curl https://ollama.ai/install.sh | sh
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curl -fsSL https://ollama.com/install.sh | sh
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```
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Or by downloading the ollama binary:
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```bash
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sudo curl -L https://ollama.ai/download/ollama-linux-amd64 -o /usr/bin/ollama
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sudo curl -L https://ollama.com/download/ollama-linux-amd64 -o /usr/bin/ollama
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sudo chmod +x /usr/bin/ollama
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```
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@ -110,6 +112,7 @@ sudo rm $(which ollama)
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```
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Remove the downloaded models and Ollama service user and group:
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```bash
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sudo rm -r /usr/share/ollama
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sudo userdel ollama
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@ -67,13 +67,13 @@ To use this:
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More examples are available in the [examples directory](../examples).
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### `Modelfile`s in [ollama.ai/library][1]
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### `Modelfile`s in [ollama.com/library][1]
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There are two ways to view `Modelfile`s underlying the models in [ollama.ai/library][1]:
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There are two ways to view `Modelfile`s underlying the models in [ollama.com/library][1]:
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- Option 1: view a details page from a model's tags page:
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1. Go to a particular model's tags (e.g. https://ollama.ai/library/llama2/tags)
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2. Click on a tag (e.g. https://ollama.ai/library/llama2:13b)
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1. Go to a particular model's tags (e.g. https://ollama.com/library/llama2/tags)
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2. Click on a tag (e.g. https://ollama.com/library/llama2:13b)
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3. Scroll down to "Layers"
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- Note: if the [`FROM` instruction](#from-required) is not present,
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it means the model was created from a local file
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@ -225,4 +225,4 @@ MESSAGE assistant yes
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- the **`Modelfile` is not case sensitive**. In the examples, uppercase instructions are used to make it easier to distinguish it from arguments.
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- Instructions can be in any order. In the examples, the `FROM` instruction is first to keep it easily readable.
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[1]: https://ollama.ai/library
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[1]: https://ollama.com/library
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@ -17,7 +17,7 @@ Prerequisites:
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Here are the steps:
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- Install Ollama via standard Linux command (ignore the 404 error): `curl https://ollama.ai/install.sh | sh`
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- Install Ollama via standard Linux command (ignore the 404 error): `curl https://ollama.com/install.sh | sh`
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- Stop the Ollama service: `sudo systemctl stop ollama`
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- Start Ollama serve in a tmux session called ollama_jetson and reference the CUDA libraries path: `tmux has-session -t ollama_jetson 2>/dev/null || tmux new-session -d -s ollama_jetson
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'LD_LIBRARY_PATH=/usr/local/cuda/lib64 ollama serve'`
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