- 09 Apr, 2025 1 commit
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Anant Sharma authored
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- 03 Apr, 2025 1 commit
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Ryan Olson authored
Moved all of `lib/llm/src/engines` to their own crates as e.g. `lib/engines/mistralrs`. This will allow publishing of the `dynamo-llm` crate as it won't have any github dependencies. The only engines in dynamo-llm will be the demo `echo` ones. Co-authored-by:Graham King <grahamk@nvidia.com>
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- 02 Apr, 2025 1 commit
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Ryan Olson authored
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- 31 Mar, 2025 1 commit
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Ryan Olson authored
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- 24 Mar, 2025 1 commit
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Graham King authored
This lets us do: ``` dynamo-run out=llamacpp <gguf_file> ``` Previously a `--model-config <hf-repo>` was also required, to configure our tokenizer.
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- 19 Mar, 2025 1 commit
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Graham King authored
This makes the Rust parts all use ring / rustls library instead of local install of openssl. It's a step on the journey to being statically linked. Pieces: - `tokenizers` and `mistralrs` now support rustls (mistralrs by default, tokenizers with feature flag). - Move shared dependencies up into workspace - New `rand` crate has some renames for future rust - Ensure the dependency doesn't creep back in by enforcing it with cargo deny.
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- 17 Mar, 2025 1 commit
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Graham King authored
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- 15 Mar, 2025 1 commit
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Graham King authored
``` dynamo-run in=batch:prompts.jsonl out=mistralrs ~/llm_models/Llama-3.2-3B-Instruct/ ``` The file has genai format, one entry per line: ``` {"text": "the prompt"} {"text": ..etc ``` The prompt is evaluated and the output written to `output.jsonl` in the same folder as the input. At the end of the run various statistics are printed: > Ran 5 files in 8s 679ms. Tokens in: 40 (5/s). Tokens out: 346 (43/s) This is also helpful for pushing load into the system and stressing the various components. Not intended for performance measurement, it's a batch inference tool.
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- 14 Mar, 2025 1 commit
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Ryan Olson authored
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- 13 Mar, 2025 3 commits
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Anant Sharma authored
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Graham King authored
"netlink" doesn't exist on Mac. We print the primary network interface to help multi-node setup, which is also unlikely on Mac.
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Graham King authored
- Any engine can take the name of a Hugging Face repository. It will be downloaded before calling the engine. - The default engine (previously always mistralrs) depends on what is compiled in. - Text can be piped in and will result in a single run of the model. All of those together mean if you build with `--features vllm` you can do this and it will download the model and run it with vllm, answer your question, and exit: ``` echo "What is the capital of Costa Rica?" | dynamo-run Qwen/Qwen2.5-3B-Instruct ``` Co-authored-by:Ryan McCormick <rmccormick@nvidia.com>
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- 11 Mar, 2025 2 commits
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Graham King authored
- Latest from repo, many improvements - Support most of the OpenAI request features (temperature, top_p, etc) - Download models from Hugging Face if necessary
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Neelay Shah authored
Co-authored-by:Meenakshi Sharma <163925564+nvda-mesharma@users.noreply.github.com>
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- 10 Mar, 2025 1 commit
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Anant Sharma authored
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- 08 Mar, 2025 1 commit
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Neelay Shah authored
Co-authored-by:Biswa Panda <biswa.panda@gmail.com>
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- 07 Mar, 2025 2 commits
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Ryan McCormick authored
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Neelay Shah authored
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- 06 Mar, 2025 1 commit
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Ryan McCormick authored
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- 05 Mar, 2025 1 commit
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Neelay Shah authored
Co-authored-by:Graham King <grahamk@nvidia.com>
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- 28 Feb, 2025 2 commits
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Graham King authored
Engine, `tio` support and docs. Proof of concept / experimental.
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Ryan McCormick authored
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- 27 Feb, 2025 1 commit
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Anant Sharma authored
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- 26 Feb, 2025 2 commits
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Paul Hendricks authored
Co-authored-by:Graham King <grahamk@nvidia.com>
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Ryan McCormick authored
Co-authored-by:Ryan Olson <rolson@nvidia.com>
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- 25 Feb, 2025 3 commits
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Graham King authored
- Setup venv ``` uv venv source .venv/bin/activate uv pip install pip uv pip install sgl-kernel --force-reinstall --no-deps uv pip install "sglang[all]==0.4.2" --find-links https://flashinfer.ai/whl/cu124/torch2.4/flashinfer/ ``` - Build: `cargo build --release --features sglang` - Run single node (make sure you're in the venv): `./tio out=sglang ~/llm_models/my_model` - Run Deepseek multi-gpu / multi-node: Node 1: ``` tio in=http out=sglang --model-path ~/llm_models/DeepSeek-R1-Distill-Llama-70B/ --tensor-parallel-size 8 --num-nodes 2 --node-rank 0 --dist-init-addr 10.217.98.122:9876 ``` Node 2: ``` tio in=none out=sglang --model-path ~/llm_models/DeepSeek-R1-Distill-Llama-70B/ --tensor-parallel-size 8 --num-nodes 2 --node-rank 1 --dist-init-addr 10.217.98.122:9876 ```
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Alec authored
Co-authored-by:aflowers <aflowers@nvidia.com>
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Neelay Shah authored
Signed-off-by:
Neelay Shah <neelays@nvidia.com> Co-authored-by:
Ryan McCormick <rmccormick@nvidia.com>
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- 24 Feb, 2025 1 commit
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Biswa Panda authored
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- 21 Feb, 2025 1 commit
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Ryan Olson authored
Signed-off-by:
Ryan Olson <ryanolson@users.noreply.github.com> Co-authored-by:
Ryan McCormick <rmccormick@nvidia.com>
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- 19 Feb, 2025 1 commit
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Thomas Montfort authored
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- 18 Feb, 2025 2 commits
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Ryan Olson authored
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GuanLuo authored
Signed-off-by:
Neelay Shah <neelays@nvidia.com> Co-authored-by:
aflowers <aflowers@nvidia.com> Co-authored-by:
Ryan McCormick <rmccormick@nvidia.com> Co-authored-by:
hongkuanz <hongkuanz@nvidia.com> Co-authored-by:
Neelay Shah <neelays@nvidia.com>
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- 13 Feb, 2025 1 commit
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Ryan Olson authored
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- 12 Feb, 2025 1 commit
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Ryan Olson authored
Signed-off-by:
Ryan Olson <ryanolson@users.noreply.github.com> Co-authored-by:
Ryan McCormick <rmccormick@nvidia.com>
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- 11 Feb, 2025 1 commit
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Anant Sharma authored
Co-authored-by:Ryan McCormick <rmccormick@nvidia.com>
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- 10 Feb, 2025 2 commits
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Ryan Olson authored
Signed-off-by:
Ryan Olson <ryanolson@users.noreply.github.com> Co-authored-by:
Ryan McCormick <rmccormick@nvidia.com>
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Ryan Olson authored
Signed-off-by:
Ryan Olson <ryanolson@users.noreply.github.com> Co-authored-by:
Ryan McCormick <rmccormick@nvidia.com> Co-authored-by:
Neelay Shah <neelays@nvidia.com>
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- 06 Feb, 2025 1 commit
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Alec authored
Co-authored-by:aflowers <aflowers@nvidia.com>
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- 04 Feb, 2025 1 commit
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Ryan Olson authored
the journey begins
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