* Pickle work-in-progress.
* More unpickling.
* More pickling.
* Proper handling of setitems.
* Clippy.
* Again more pickling.
* Restore the example.
* Add enough pickle support to get the list of tensors.
* Read the data from zip files.
* Retrieve the tensor shape.
* Extract the size and dtype.
* More storage types.
* Improve the destructuring.
* Also support ggml files.
* Pickle work-in-progress.
* More unpickling.
* More pickling.
* Proper handling of setitems.
* Clippy.
* Again more pickling.
* Restore the example.
* Add enough pickle support to get the list of tensors.
* Read the data from zip files.
* Retrieve the tensor shape.
* Extract the size and dtype.
* More storage types.
* Improve the destructuring.
* Add a vision transformer example (dino-v2).
* Add some documentation + test.
* CI fix.
* Another fix (still unable to replicate the errors locally :( )
* Print the detected arch options.
* Add the q6k quantization.
* Add a currently broken test.
* Bugfix.
* Bugfix.
* Another bugfix.
* Another bugfix + get the test to work.
* Add more stats to the ggml example.
* Build a quantized model from the file content.
* Move the tensor retrieval in the main crate.
* Start adding the forward pass.
* Add more to the forward pass of the quantized llama.
* Apply the attention layers.
* Add the sampling loop.
* Get the sampling loop to work.
* Minor tweak.
* Add a quantize/dequantize test.
* Bugfix.
* Add a comment + swap the order.
* Bugfixes.
* Properly initialize wdata.
* Simplify the matmul bits.
* Add from_float for q4_0.
* Fix a couple bugs.
* Get the test to work.
* Get clippy to be happy.
* Add a vecdot trait.
* Start implementing mul_mat.
* Add to the mul mat implementation.
* Add q8_0 quantization.
* Implement the GgmlType trait for all types.
* Add the missing block.
* Add a TODO.
* Add a cudnn feature to be used for conv2d.
* Allocate the proper workspace.
* Only create a single cudnn handle per cuda device.
* Proper cudnn usage.
* Bugfix.
* Add a cuda kernel for avg-pool2d.
* Avoid running out of bounds.
* Finish wiring the avg pool kernel + add some testing.
* Support for max-pool + testing.
* Add a naive conv2d cuda kernel.
* Proper conv2d support on the rust side.
* Conv1d testing on gpu.
* Also use the test on gpus.
* Fix the clean-ptx target.
* Track the conv2d operations in stable-diffusion.
* Add more tracing to stable-diffusion.
* Also trace the resnet bits.
* Trace the attention blocks.
* Also trace the attention inner part.
* Small tweak.
* Add more tracing to the whisper example.
* Support accelerate in more examples.
* Use accelerate for pointwise functions.
* Use accelerate for binary operations too.
* Bugfix for binary operation: use the rhs before the lhs.
* Change distributions
Standard generates in [0, 1), Normal is correct.
* Add test
Not sure if this is the best place to put the test
* Remove unnecessary use
