Add QuantizedEmbedding and EmbeddingLayer interface so models can
use quantized embedding weights and expose tied output projections.
This change updates gemma3, glm4_moe_lite, llama, qwen3, and qwen3_5
to use the new interface.
This change adds a tensorImportTransform interface for model-specific
tensor transformations during safetensors import. This allows importing
and modifying the standard HF based weights as well as the mlx-community
derived pre-quantized safetensors repos to be directly
imported into `ollama create`. Right now this only works with Qwen3.5
importing which does tensor renaming, norm weight shifting (it
adds +1 to each value of the norm vectors), conv1d transposition,
and casts to BF16s for F32 based vectors.
- Collapse MLX sampling state into a single sample.Sampler struct (options + history).
- Replace interface-based sampler chain (TopP, TopK, penalty, etc.) with function-based transforms.
- Update request/pipeline wiring to use *sample.Sampler, seed history from prompt tokens, and append generated tokens each step.
- Implement top_p, min_p, repeat_penalty, and frequency_penalty
This change adds support for qwen3.5-next-moe models (qwen3-next/qwen3.5-next/qwen3-coder) to the MLX runner. It also:
* introduces recurrent cache support and related MLX ops
* updates pipeline/runner integration and adds tests
* properly quantizes stacked expert tensors
* a Gated Delta Metal kernel for fast SSM inference
* adds new MLX calls for Conv1d, DepthwideConv1d, Contiguous, Exp, Log, SoftmaxAxis
This change adds a new x/tokenizer package which includes:
* New BPE and SentencePiece tokenizers
* Removing the dependency on the imagegen tokenizers
* Fixes to multibyte decoding in the pipeline
* Various correctness and benchmark tests
Not included in this PR is the WordPiece tokenizer for BERT models which will be
added when we add embedding models. The imagegen tokenizers will also be removed in
a follow-up PR.
This fixes a bug with current MLX based models which don't get loaded/unloaded correctly. The first model currently gets loaded and then subsequent model starts get shunted to the first runner which results in the wrong model being run.
This change fixes an issue where GGML based models (for either the Ollama runner or
the legacy llama.cpp runner) would try to load the mlx library. That would panic
and the model fails to start.
This change adds a new MLX based runner which includes:
* Method-based MLX bindings
* Subprocess-based MLX runner (x/mlxrunner)
* KV cache with tree management
* A basic sampler
The GLM4-MoE-Lite model has been ported to use the new bindings.
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Co-authored-by: Michael Yang <git@mxy.ng>
This change includes:
- changes to the safetensors metadata format
- changes to the create command to properly create the blobs with the new format
- changes to load the new format
- fixes ollama show to properly show each tensor
* x: make `ollama create --experimental` import from safetensors
This change allows pulling in safetensors models into the new experimental model format, and also
fixes the `ollama show` command to be able to correctly display the model information.
* gofumpt the linter
* gofumpt the linter again
* validate the model name
This change:
* fixes rope scaling in the mistral converter
* updates ministral to include llama4 scaling
* includes a new ministral parser for parsing reasoning and tool calling
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Co-authored-by: jmorganca <jmorganca@gmail.com>
This change adds a basic benchmarking test framework for Ollama which can
be used to determine the prefill, eval, load duration, and total duration
for running a given model or models.
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
This change moves back to converting bf16 vision weights to fp16,
specifically if they start with the name "v." (such as v.blk.0.attn_k.weight).
This fixes a bug where converted images are failing because they are trying
to call `im2col` which doesn't have a bf16 kernel in ggml.
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
Patrick Devine