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* Add a Context trait similar to anyhow::Context.
* Switch two unwrap to context.
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* module docs
* varbuilder gguf docs
* add a link to gguf files
* small additonal mod doc titles
* safetensor docs
* more core docs
* more module docs in canlde_core
* 2 more link fixes
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* Support for UG kernels.
* Add a dedicated test.
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* Metal part 1 - Scaffolding for metal.
* Remove tracing.
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* Implemented meshgrid
* Resolved feedback from LaurentMazare
* Rustfmt
* Updated docstring
* Removed outdated error mode from docstring
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* Start processing images.
* Add LayerNorm2d.
* Properly use LayerNorm2d.
* Tweak eps.
* Use LayerNorm on inputs with a rank different from 3.
* Window partitioning.
* Fix a couple todos.
* More todos.
* Hard-code the einsums.
* More padding support.
* Some sizes tweaks.
* Use the hub to get the weights.
* Use a batch matmul.
* Tweaks.
* More fixes.
* Get some predictions to be generated.
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* img2img pipeline for stable diffusion.
* Rename the arguments + fix.
* Fix for zero strength.
* Another fix.
* Another fix.
* Revert.
* Include the backtrace.
* Noise scaling.
* Fix the height/width.
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* 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.
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* Simplify the npy writing.
* Wrap the file path so as to provide better errors.
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* Rework the commands and run inference by default.
* Add the training module and load the training dataset.
* Random dataset iterator.
* Proper valid-loss computation.
* Compute the evaluation loss.
* Add more substance to the training loop.
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* Use bail rather than wrapping a string where possible.
* Revert the cuda default bit.
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* Proper flash-attn parameters.
* Set the flash attention parameters.
* Add more validations.
* Setup the o_ flash attn parameters.
* More flash-attn support.
* Set more flash attn parameters.
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* Add the cpu version of index-add.
* More cpu support for index-add.
* Use index-add in the backprop.
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* Refactor the reduce ops in order to introduce argmin/argmax.
* Clippy fixes.
* Use the newly introduced argmax.
* Fix the strided case.
* Handle the non-contiguous case.
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* Add the index-select op.
* Cpu implementation of index-select.
* Add the cpu implementation for index-select.
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* Add cpu support for min and max.
* Add min/max all.
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* Add backtrace information to errors where relevant.
* More backtrace information.
* Add to the FAQ.
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* Move the variable creation to the variable module.
* Make it possible to set a variable.
* Add some basic gradient descent test.
* Get the gradient descent test to work.
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* Use a rw-lock.
* Make clippy happier.
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* Working towards tensor mutability.
* Use a ref-cell to provide tensor mutability.
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* Sketch the candle-transformers crate.
* Format the empty files.
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* Cosmetic cleanups to the error enum.
* More error cleanup.
* Proper error handling rather than panicing.
* Add some conv1d dedicated error.
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* Add some trait to formalize backends.
* Use the generic backend trait.
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