When trying to use cloud model with OLLAMA_HOST="ollama.com" while not signed in a helpful error message is displayed when the user is not signed in telling them they must sign in to use cloud models. This should be the same experience for models which specify a remote instance.
TeaCache:
- Timestep embedding similarity caching for diffusion models
- Polynomial rescaling with configurable thresholds
- Reduces transformer forward passes by ~30-50%
FP8 quantization:
- Support for FP8 quantized models (8-bit weights with scales)
- QuantizedMatmul on Metal, Dequantize on CUDA
- Client-side quantization via ollama create --quantize fp8
Other bug fixes:
- Fix `/api/show` API for image generation models
- Server properly returns model info (architecture, parameters, quantization)
- Memory allocation optimizations
- CLI improvements for image generation
Co-authored-by: A-Akhil <akhilrahul70@gmail.com>
This PR introduces a new ollama embed command that allows users to generate embeddings directly from the command line.
Added ollama embed MODEL [TEXT...] command for generating text embeddings
Supports both direct text arguments and stdin piping for scripted workflows
Outputs embeddings as JSON arrays (one per line)
There are two bugs when using `/load <model>` for a model that doesn't exist, namely:
1. it will not restore the current model settings if the current model is a thinking model; and
2. it will crash is the current model is a non-thinking model
This bug fix saves the current runOptions and then restores them if the model load
doesn't happen. It also fixes the crash happening for non-thinking models.
* auth: fix problems with the ollama keypairs
This change adds several fixes including:
- reading in the pubkey files correctly
- fixing the push unit test to create a keypair file in a temp directory
- not return 500 errors for normal status error
With support for multimodal models becoming more varied and common it is important for clients to be able to easily see what capabilities a model has. Retuning these from the show endpoint will allow clients to easily see what a model can do.
This fixes the case where a FROM line in previous modelfile points to a
file which may/may not be present in a different ollama instance. We
shouldn't be relying on the filename though and instead just check if
the FROM line was instead a valid model name and point to that instead.
Add metadata and tensor information to the show command to be able to
see more information about a model. This outputs the same data as
shown on the model details page on ollama.com
After a user pushes their model it is not clear what to do next. Add a link
to the output of `ollama push` that tells the user where their model can now
be found.
