Ollama
Notes
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 runis 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
chatorinstructmodels now support setting thesystemparameter, orSYSTEMcommand in theModelfile - Parameters (
num_ctx, etc) have been updated for library models - Slight performance improvements for all models
- All
- Model storage can now be configured with
OLLAMA_MODELS. See the FAQ for more info on how to configure this. OLLAMA_HOSTwill now default to port443whenhttps://is specified, and port80whenhttp://is specified- Fixed trailing slashes causing an error when using
OLLAMA_HOST - Fixed issue where
ollama pullwould retry multiple times when out of space - Fixed various
out of memoryissues when using Nvidia GPUs - Fixed performance issue previously introduced on AMD CPUs
New Contributors
- @ajayk made their first contribution in https://github.com/jmorganca/ollama/pull/855
Full Changelog: https://github.com/jmorganca/ollama/compare/v0.1.5...v0.1.6