v0.1.9

New models

• Yi: a high-performing, bilingual model supporting both English and Chinese.

What's Changed

• JSON mode: instruct models to always return valid JSON when calling /api/generate by setting the format parameter to json
• Raw mode: bypass any templating done by Ollama by passing {"raw": true} to /api/generate
• Better error descriptions when downloading and uploading models with ollama pull and ollama push
• Fixed issue where Linux installer would encounter an error when running as the root user
• Improved progress bar design when running ollama pull and ollama push
• Fixed issue where running on a machine with less than 2GB of VRAM would be slow

New Contributors

• @pepperoni21 made their first contribution in #995
• @lgrammel made their first contribution in #1020
• @ej52 made their first contribution in #999
• @David-Kunz made their first contribution in #996
• @tjbck made their first contribution in #943
• @omagdy7 made their first contribution in #1029
• @upchui made their first contribution in #1034
• @kevinhermawan made their first contribution in #1043
• @amithkoujalgi made their first contribution in #1044
• @mpldr made their first contribution in #1042
• @aashish2057 made their first contribution in #992
• @nickanderson made their first contribution in #1062

Full Changelog: v0.1.8...v0.1.9

v0.1.8

New Models

• CodeBooga: A high-performing code instruct model created by merging two existing code models.
• Dolphin 2.2 Mistral: An instruct-tuned model based on Mistral. Version 2.2 is fine-tuned for improved conversation and empathy.
• MistralLite: MistralLite is a fine-tuned model based on Mistral with enhanced capabilities of processing long contexts.
• Yarn Mistral an extension of Mistral to support a context window of up to 128 tokens
• Yarn Llama 2 an extension of Llama 2 to support a context window of up to 128 tokens

What's Changed

• Ollama will now honour large context sizes on models such as codellama and mistrallite
• Fixed issue where repeated characters would be output on long contexts
• ollama push is now much faster. 7B models will push up to ~100MB/s and large models (70B+) up to 1GB/s if network speeds permit

New Contributors

• @dloss made their first contribution in #948
• @noahgitsham made their first contribution in #983

Full Changelog: v0.1.7...v0.1.8

v0.1.7

What's Changed

• Fixed an issue when running ollama run where certain key combinations such as Ctrl+Space would lead to an unresponsive prompt
• Fixed issue in ollama run where retrieving the previous prompt from history would require two up arrow key presses instead of one
• Exiting ollama run with Ctrl+D will now put cursor on the next line

Full Changelog: v0.1.6...v0.1.7

v0.1.6

New models

• Dolphin 2.1 Mistral: an instruct-tuned model based on Mistral and trained on a dataset filtered to remove alignment and bias.
• Zephyr Beta: this is the second model in the series based on Mistral, and has strong performance that compares to and even exceeds Llama 2 70b in several categories. It’s trained on a distilled dataset, improving grammar and yielding even better chat results.

What's Changed

• Pasting multi-line strings in ollama run is now possible
• Fixed various issues when writing prompts in ollama run
• The library models have been refreshed and revamped including llama2, codellama, and more:
  • All chat or instruct models now support setting the system parameter, or SYSTEM command in the Modelfile
  • Parameters (num_ctx, etc) have been updated for library models
  • Slight performance improvements for all models
• Model storage can now be configured with OLLAMA_MODELS. See the FAQ for more info on how to configure this.
• OLLAMA_HOST will now default to port 443 when https:// is specified, and port 80 when http:// is specified
• Fixed trailing slashes causing an error when using OLLAMA_HOST
• Fixed issue where ollama pull would retry multiple times when out of space
• Fixed various out of memory issues when using Nvidia GPUs
• Fixed performance issue previously introduced on AMD CPUs

New Contributors

• @ajayk made their first contribution in #855

Full Changelog: v0.1.5...v0.1.6

v0.1.5

What's Changed

• Fix an issue where an error would occur when running falcon or starcoder models

Full Changelog: v0.1.4...v0.1.5

v0.1.4

New models

• OpenHermes 2 Mistral: a new fine-tuned model based on Mistral, trained on open datasets totalling over 900,000 instructions. This model has strong multi-turn chat skills, surpassing previous Hermes 13B models and even matching 70B models on some benchmarks.

What's Changed

• Faster model switching: models will now stay loaded between requests when using different parameters (e.g. temperature) or system prompts
• starcoder, sqlcoder and falcon models now have unicode support. Note: they will need to be re-pulled (e.g. ollama pull starcoder)
• New documentation guide on importing existing models to Ollama (GGUF, PyTorch, etc)
• ollama serve will now print the current version of Ollama on start
• ollama run will now show more descriptive errors when encountering runtime issues (such as insufficient memory)
• Fixed an issue where Ollama on Linux would use CPU instead of using both the CPU and GPU for GPUs with less memory
• Fixed architecture check in Linux install script
• Fixed issue where leading whitespaces would be returned in responses
• Fixed issue where ollama show would show an empty SYSTEM prompt (instead of omitting it)
• Fixed issue with the /api/tags endpoint would return null instead of [] if no models were found
• Fixed an issue where ollama show wouldn't work when connecting remotely by using OLLAMA_HOST
• Fixed issue where GPU/Metal would be used on macOS even with num_gpu set to 0
• Fixed issue where certain characters would be escaped in responses
• Fixed ollama serve logs to report the proper amount of GPU memory (VRAM) being used

Note: the EMBED keyword in Modelfile is being revisited until a future version of Ollama. Join the discussion on how we can make it better.

New Contributors

• @vieux made their first contribution in #810
• @s-kostyaev made their first contribution in #801
• @ggozad made their first contribution in #794
• @awaescher made their first contribution in #811
• @deichbewohner made their first contribution in #799

Full Changelog: v0.1.3...v0.1.4

v0.1.3

What's Changed

• Improved various API error messages to be easier to read
• Improved GPU allocation for older GPUs to fix "out of memory" errors
• Fixed issue where setting num_gpu to 0 would result in an error
• Ollama for macOS will now always update to the latest version, even if earlier updates had also been downloaded beforehand

Full Changelog: v0.1.2...v0.1.3

v0.1.2

New Models

• Zephyr A fine-tuned 7B version of mistral that was trained on a mix of publicly available, synthetic datasets and performs as well as Llama 2 70B in many benchmarks
• Mistral OpenOrca a 7 billion parameter model fine-tuned on top of the Mistral 7B model using the OpenOrca dataset

Examples

Ollama's examples have been updated with some new examples:

• Ask the mentors: a TypesScript, multi-user conversation app
• TypeScript LangChain: a simple example of using Ollama with LangChainJS and TypeScript.

What's Changed

• Download speeds for ollama pull have been significantly improved, from 60MB/s to over 1.5GB/s (25x faster) on fast network connections
• The API now supports non-streaming responses. Set the stream parameter to false and endpoints will return data in one single response:

  curl -X POST http://localhost:11434/api/generate -d '{
    "model": "llama2",
    "prompt": "Why is the sky blue?",
    "stream": false
  }'
  

• Ollama can now be used with http proxies (using HTTP_PROXY=http://<proxy>) and https proxies (using HTTPS_PROXY=https://<proxy>)
• Fixed token too long error when generating a response
• q8_0, q5_0, q5_1, and f32 models will now use GPU on Linux
• Revise help text in ollama run to be easier to read
• Rename runner subprocess to ollama-runner
• ollama create will now show feedback when reading model metadata
• Fix not found error showing when running ollama pull
• Improved video memory allocation on Linux to fix errors when using Nvidia GPUs

New Contributors

• @xyproto made their first contribution in #705
• @konsalex made their first contribution in #741

Full Changelog: v0.1.1...v0.1.2

v0.1.1

What's Changed

• Cancellable responses: Ctrl+C will now cancel responses when running ollama run
• Exit ollama run sessions with Ctrl+D or /bye
• Improved error messages for unknown /slash commands when using ollama run
• Various improvements to the Linux install script for distro compatibility and to fix bugs
• Fixed install issues on Fedora
• Fixed issue where specifying the library/ prefix in ollama run would cause an error
• Fixed highlight color for placeholder text in ollama run
• Fixed issue where auto updater would not restart when clicking "Restart to Update"
• Ollama will now clean up subdirectories in ~/.ollama/models
• Ollama when now show a default message when ollama show results in an empty message

New Contributors

• @aaroncoffey made their first contribution in #629
• @lstep made their first contribution in #621
• @JayNakrani made their first contribution in #632
• @jimexist made their first contribution in #664
• @hallh made their first contribution in #663

Full Changelog: v0.1.0...v0.1.1

v0.1.0

Ollama for Linux

Ollama for Linux is now available, with GPU acceleration enabled out-of-the-box for Nvidia GPUs.

💯 Ollama will run on cloud servers with multiple GPUs attached
🤖 Ollama will run on WSL 2 with GPU support
😍 Ollama maximizes the number of GPU layers to load to increase performance without crashing
🤩 Ollama will support CPU only, and small hobby gaming GPUs to super powerful workstation graphics cards like the H100

Download

curl https://ollama.ai/install.sh | sh

Manual install steps are also available.

Changelog

• Ollama will now automatically offload as much of the running model as is supported by your GPU for maximum performance without any crashes
• Fix issue where characters would be erased when running ollama run
• Added a new community project by @TwanLuttik in #574

New Contributors

• @TwanLuttik made their first contribution in #574

Full Changelog: v0.0.21...v0.1.0