* moondream implementation
* add moondream example
* change config default activation
* Add assets and integrate phi mixformer with example
* Make use of kv cache and fix seq_len bug; Clean up example code
* Add README link to example
* Remove pos_embed scaling; Remove assets; Add to README; Expand VisionConfig
* Delete image
* Use apply instead of forward
* Use latest release special token; Fix token/s accuracy; Use GeluPytorchTanh in VisionConfig v2
* moondream implementation
* add moondream example
* change config default activation
* Add assets and integrate phi mixformer with example
* Make use of kv cache and fix seq_len bug; Clean up example code
* Add README link to example
* Remove pos_embed scaling; Remove assets; Add to README; Expand VisionConfig
* Delete image
* Use apply instead of forward
* Pass bos token at the beginning of tensor.
* Quantize moondream.
* Forward with image bos token.
* Clippy.
* Use q4_0 quantization.
* Add pointers for sequence and tokens; Remove seq_len conditional
* moondream implementation
* add moondream example
* change config default activation
* Add assets and integrate phi mixformer with example
* Make use of kv cache and fix seq_len bug; Clean up example code
* Add README link to example
* Remove pos_embed scaling; Remove assets; Add to README; Expand VisionConfig
* Delete image
* Use apply instead of forward
* CLIP model implementation with example
* CLIP Implementation fixes, batch images
* CLIP model remove images from git
* CLIP model remove unnecessary use of batch_indices
* Fast kernels for rotary embeddings.
* Add a test for the fast CPU kernel.
* Rope cuda bindings.
* Cuda kernel.
* Metal kernel (part 1).
* Cuda kernels.
* Finish the metal kernel.
* Use the new kernels in the quantized example.
* Fix warning.
* Avoid copying the data on squeeze and unsqueeze.
* Fix the quantized llama example.
* Unrelated fix for the quantized stable-lm example on cuda.
* Fix for mamba on cuda (unrelated to the PR).
* Add the metavoice transformer.
* Sketch the speaker-encoder module.
* Adding to the metavoice model.
* Start adding the metavoice example.
* Get some logits out.
* Load the second stage model.
* Get the second step to run.
* Tweak the example.
* Add encodec tilting.
* Glue the different bits together.
* Fix a shape issue.
* Use a constant.
* BPE tokenization.
* Add a warning.
* Encodec model.
* Fixes.
* Add the padding functions.
* Get the LSTM bit to work.
* Get the encodec model to generate some tokens (decoder only for now).
* Minor tweak.
* Minor tweak.
* and quantized rwkv v5 model
* Integrate the quantized rwkv model in the initial example.
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Co-authored-by: laurent <laurent.mazare@gmail.com>
