* Update Quantization docs and minor doc fix.
* update readme with latest quants info
* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* up
---------
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* feat: first draft load multiple lora
* feat: load weights within layer and refactor lora pass
* fix: refactor and reduce lora math
* feat: baseline impl single request multi lora support
* feat: prefer lorax implementation and port loading logic
* fix: prefer adapter_data and refactors
* feat: perfer loraxs custom punica kernels and add mlp loras
* fix: adjust batch for bgmv
* fix: adjust adapter_segments logic when in batch
* fix: refactor and move changes to v3 proto
* fix: pass model_id for all flash causal lms
* fix: pass model_id for all causal and seq2seq lms
* fix: add model_id to model test
* feat: add lora support to mistral and refactors
* feat: prefer model id in request
* fix: include rust code for adapter id
* feat: bump launcher and add new lora docs
* feat: support base model generation and refactors
* fix: rename doc to retry ci build
* feat: support if vlm models
* fix: add adapter_data param and avoid missing layers
* fix: add adapter_data param to phi and neox
* fix: update all models forwards to include adapter_data
* fix: add model_id to IdeficsCausalLM
* Update lora.md
Fixed a typo
* Update lora.md
Fixing spam image
* fix: add lora kernel to dockerfile, support running without kernels and refactors
* fix: avoid dockerfile conflict
* fix: refactors and adjust flash llama lora logic
* fix: skip llama test due to CI issue (temp)
* fix: skip llama test CI (temp) 2
* fix: revert skips and prefer updated ci token for tests
* fix: refactors and helpful comments
* fix: add noop in TensorParallelAdapterRowLinear too
* fix: refactor and move shard_lora_weights logic
* fix: exit early if no adapter_data
---------
Co-authored-by: Derek <datavistics@gmail.com>
Mostly straightforward, changes to existing code:
* Wrap quantizer parameters in a small wrapper to avoid passing
around untyped tuples and needing to repack them as a dict.
* Move scratch space computation to warmup, because we need the
maximum input sequence length to avoid allocating huge
scratch buffers that OOM.
- Axum upgraded to hyper 1.0 and most of the ecosystem switched so it's
our time now
- [ngrok-rust](https://github.com/ngrok/ngrok-rust/pull/137/files)
hasn't yet, and hasn't for several months now, so let's disabled the
feature for the time being.
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This PR adds a tutorial to self distill and train medusa heads for a
specific model
---------
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
This PR adds a short "how it works" section to guidance and includes a
mention to the outlines library that enables grammars/tools
*and a small formatting change
---------
Co-authored-by: Mishig <mishig.davaadorj@coloradocollege.edu>
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compliation -> compilation
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It was meant to be in seconds float
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Just removed `--` from the arguments.
With `--` bitsandbytes and bitsandbytes-nf4 are considered an option
which they are not
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IDK what else to add in this guide, I looked for relevant code in TGI
codebase and saw that it's used in quantization as well (maybe I could
add that?)
PR for conceptual guide on flash attention. I will add more info unless
I'm told otherwise.
---------
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>
OlivierDehaene