diff --git a/Dockerfile b/Dockerfile index aaae495ea44..8573be3a5d1 100644 --- a/Dockerfile +++ b/Dockerfile @@ -41,7 +41,7 @@ COPY launcher launcher RUN cargo build --profile release-opt # Text Generation Inference base image -FROM vault.habana.ai/gaudi-docker/1.17.0/ubuntu22.04/habanalabs/pytorch-installer-2.3.1:latest as base +FROM vault.habana.ai/gaudi-docker/1.18.0/ubuntu22.04/habanalabs/pytorch-installer-2.4.0:latest as base ENV ATTENTION=default ENV PREFIX_CACHING=0 @@ -75,7 +75,7 @@ RUN cd server && \ make gen-server && \ pip install -r requirements.txt && \ bash ./dill-0.3.8-patch.sh && \ - pip install git+https://github.com/HabanaAI/DeepSpeed.git@1.17.0 && \ + pip install git+https://github.com/HabanaAI/DeepSpeed.git@1.18.0 && \ BUILD_CUDA_EXT=0 pip install git+https://github.com/AutoGPTQ/AutoGPTQ.git@097dd04e --no-build-isolation && \ pip install . --no-cache-dir diff --git a/README.md b/README.md index e91b72d603a..bf9a9f20a95 100644 --- a/README.md +++ b/README.md @@ -20,6 +20,7 @@ limitations under the License. - [Text Generation Inference on Habana Gaudi](#text-generation-inference-on-habana-gaudi) - [Table of contents](#table-of-contents) + - [Tested Models and Configurations](#tested-models-and-configurations) - [Running TGI on Gaudi](#running-tgi-on-gaudi) - [TGI-Gaudi Benchmark](#tgi-gaudi-benchmark) - [Static Batching Benchmark](#static-batching-benchmark) @@ -32,24 +33,46 @@ limitations under the License. - [Llama3.1-70B 8 cards](#llama31-70b-8-cards) - [Llava-v1.6-Mistral-7B on 1 card](#llava-v16-mistral-7b-on-1-card) - [Running TGI with FP8 Precision](#running-tgi-with-fp8-precision) - - [Llama2-7B on 1 Card](#llama2-7b-on-1-card-1) - - [Llama2-70B on 8 Cards](#llama2-70b-on-8-cards-1) - - [Llama3.1-8B on 1 Card](#llama31-8b-on-1-card-1) - - [Llama3.1-70B on 8 cards](#llama31-70b-on-8-cards) - - [Llava-v1.6-Mistral-7B on 1 Card](#llava-v16-mistral-7b-on-1-card-1) - - [Llava-v1.6-Mistral-7B on 8 Cards](#llava-v16-mistral-7b-on-8-cards) + - [TGI-Gaudi Benchmark](#tgi-gaudi-benchmark) - [Adjusting TGI Parameters](#adjusting-tgi-parameters) - [Environment Variables](#environment-variables) - [Profiler](#profiler) - [License](#license) + +## Tested Models and Configurations + +The following table contains models and configurations we have validated on Gaudi2. + + +|  Model |  BF16 | |  FP8 | | +| ---------------------- | ------------ | ----------- | ------------ | ----------- | +| |  Single Card |  Multi-Card |  Single Card |  Multi-Card | +|  Llama2-7B |  ✔ |  ✔ |  ✔ |  ✔ | +|  Llama2-70B | |  ✔ | |  ✔ | +|  Llama3-8B |  ✔ |  ✔ |  ✔ |  ✔ | +|  Llama3-70B | |  ✔ | |  ✔ | +|  Llama3.1-8B |  ✔ |  ✔ |  ✔ |  ✔ | +|  Llama3.1-70B | |  ✔ | |  ✔ | +|  CodeLlama-13B |  ✔ |  ✔ |  ✔ |  ✔ | +|  Mixtral-8x7B |  ✔ |  ✔ |  ✔ |  ✔ | +|  Mistral-7B |  ✔ |  ✔ |  ✔ |  ✔ | +|  Falcon-180B | |  ✔ | |  ✔ | +|  Qwen2-72B | |  ✔ | |  ✔ | +|  Starcoder2-3b |  ✔ |  ✔ |  ✔ | | +|  Starcoder2-15b |  ✔ |  ✔ |  ✔ | | +|  Starcoder |  ✔ |  ✔ |  ✔ |  ✔ | +|  Gemma-7b |  ✔ |  ✔ |  ✔ |  ✔ | +|  Llava-v1.6-Mistral-7B |  ✔ |  ✔ |  ✔ |  ✔ | + + ## Running TGI on Gaudi To use [🤗 text-generation-inference](https://github.com/huggingface/text-generation-inference) on Habana Gaudi/Gaudi2/Gaudi3, follow these steps: 1. Pull the official Docker image with: ```bash - docker pull ghcr.io/huggingface/tgi-gaudi:2.3.1 + docker pull ghcr.io/huggingface/tgi-gaudi:2.0.6 ``` > [!NOTE] > Alternatively, you can build the Docker image using the `Dockerfile` located in this folder with: @@ -70,7 +93,7 @@ To use [🤗 text-generation-inference](https://github.com/huggingface/text-gene -e OMPI_MCA_btl_vader_single_copy_mechanism=none -e HF_TOKEN=$hf_token \ -e ENABLE_HPU_GRAPH=true -e LIMIT_HPU_GRAPH=true -e USE_FLASH_ATTENTION=true \ -e FLASH_ATTENTION_RECOMPUTE=true --cap-add=sys_nice --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 --model-id $model --max-input-tokens 1024 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 --model-id $model --max-input-tokens 1024 \ --max-total-tokens 2048 ``` @@ -84,7 +107,7 @@ To use [🤗 text-generation-inference](https://github.com/huggingface/text-gene -e HABANA_VISIBLE_DEVICES=all -e OMPI_MCA_btl_vader_single_copy_mechanism=none \ -e HF_TOKEN=$hf_token -e ENABLE_HPU_GRAPH=true -e LIMIT_HPU_GRAPH=true \ -e USE_FLASH_ATTENTION=true -e FLASH_ATTENTION_RECOMPUTE=true --cap-add=sys_nice \ - --ipc=host ghcr.io/huggingface/tgi-gaudi:2.3.1 --model-id $model --sharded true \ + --ipc=host ghcr.io/huggingface/tgi-gaudi:2.0.6 --model-id $model --sharded true \ --num-shard 8 --max-input-tokens 1024 --max-total-tokens 2048 ``` 3. Wait for the TGI-Gaudi server to come online. You will see something like so: @@ -98,36 +121,6 @@ To use [🤗 text-generation-inference](https://github.com/huggingface/text-gene ``` 4. Please note that the model warmup can take several minutes, especially for FP8 inference. To minimize this time in consecutive runs, please refer to [Disk Caching Eviction Policy](https://docs.habana.ai/en/latest/PyTorch/Model_Optimization_PyTorch/Optimization_in_PyTorch_Models.html#disk-caching-eviction-policy). -### TGI-Gaudi Benchmark - -#### Static Batching Benchmark - To run static batching benchmark, please refer to [TGI's benchmark tool](https://github.com/huggingface/text-generation-inference/tree/main/benchmark). - - To run it on the same machine, you can do the following: - * `docker exec -it bash` , pick the docker started from step 2 using docker ps - * `text-generation-benchmark -t ` , pass the model-id from docker run command - * after the completion of tests, hit ctrl+c to see the performance data summary. - -#### Continuous Batching Benchmark - To run continuous batching benchmark, please refer to [README in examples folder](https://github.com/huggingface/tgi-gaudi/blob/habana-main/examples/README.md). - -### Tested Models and Configurations - -The following table contains models and configurations we have validated on Gaudi2. - -| Model | BF16 | FP8 | Single Card | Multi-Cards | -|-----------------------|------|-----|-------------|-------------| -| Llama2-7B | ✔ | ✔ | ✔ | ✔ | -| Llama2-70B | ✔ | ✔ | | ✔ | -| Llama3-8B | ✔ | ✔ | ✔ | ✔ | -| Llama3-70B | ✔ | ✔ | | ✔ | -| Llama3.1-8B | ✔ | ✔ | ✔ | ✔ | -| Llama3.1-70B | ✔ | ✔ | | ✔ | -| CodeLlama-13B | ✔ | ✔ | ✔ | | -| Mixtral-8x7B | ✔ | ✔ | ✔ | ✔ | -| Mistral-7B | ✔ | ✔ | ✔ | ✔ | -| Llava-v1.6-Mistral-7B | ✔ | ✔ | ✔ | ✔ | - ## Running TGI with BF16 Precision @@ -157,7 +150,7 @@ docker run -p 8080:80 \ -e FLASH_ATTENTION_RECOMPUTE=true \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --max-input-length 1024 --max-total-tokens 2048 \ --max-batch-prefill-tokens 2048 --max-batch-total-tokens 65536 \ @@ -189,7 +182,7 @@ docker run -p 8080:80 \ -e FLASH_ATTENTION_RECOMPUTE=true \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --sharded true --num-shard 8 \ --max-input-length 1024 --max-total-tokens 2048 \ @@ -221,7 +214,7 @@ docker run -p 8080:80 \ -e FLASH_ATTENTION_RECOMPUTE=true \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --max-input-length 1024 --max-total-tokens 2048 \ --max-batch-prefill-tokens 2048 --max-batch-total-tokens 65536 \ @@ -253,7 +246,7 @@ docker run -p 8080:80 \ -e FLASH_ATTENTION_RECOMPUTE=true \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --sharded true --num-shard 8 \ --max-input-length 1024 --max-total-tokens 2048 \ @@ -285,7 +278,7 @@ docker run -p 8080:80 \ -e BATCH_BUCKET_SIZE=1 \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --max-input-tokens 4096 --max-batch-prefill-tokens 16384 \ --max-total-tokens 8192 --max-batch-total-tokens 32768 @@ -336,7 +329,7 @@ docker run -p 8080:80 \ -e FLASH_ATTENTION_RECOMPUTE=true \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --max-input-length 1024 --max-total-tokens 2048 \ --max-batch-prefill-tokens 2048 --max-batch-total-tokens 65536 \ @@ -371,7 +364,7 @@ docker run -p 8080:80 \ -e FLASH_ATTENTION_RECOMPUTE=true \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --sharded true --num-shard 8 \ --max-input-length 1024 --max-total-tokens 2048 \ @@ -407,7 +400,7 @@ docker run -p 8080:80 \ -e FLASH_ATTENTION_RECOMPUTE=true \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --max-input-length 1024 --max-total-tokens 2048 \ --max-batch-prefill-tokens 2048 --max-batch-total-tokens 65536 \ @@ -442,7 +435,7 @@ docker run -p 8080:80 \ -e FLASH_ATTENTION_RECOMPUTE=true \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --sharded true --num-shard 8 \ --max-input-length 1024 --max-total-tokens 2048 \ @@ -475,7 +468,7 @@ docker run -p 8080:80 \ -e BATCH_BUCKET_SIZE=1 \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --max-input-tokens 4096 --max-batch-prefill-tokens 16384 \ --max-total-tokens 8192 --max-batch-total-tokens 32768 @@ -506,13 +499,28 @@ docker run -p 8080:80 \ -e BATCH_BUCKET_SIZE=1 \ --cap-add=sys_nice \ --ipc=host \ - ghcr.io/huggingface/tgi-gaudi:2.3.1 \ + ghcr.io/huggingface/tgi-gaudi:2.0.6 \ --model-id $model \ --sharded true --num-shard 8 \ --max-input-tokens 4096 --max-batch-prefill-tokens 16384 \ --max-total-tokens 8192 --max-batch-total-tokens 32768 ``` +## TGI-Gaudi Benchmark + +### Static Batching Benchmark + To run static batching benchmark, please refer to [TGI's benchmark tool](https://github.com/huggingface/text-generation-inference/tree/main/benchmark). + + To run it on the same machine, you can do the following: + * `docker exec -it bash` , pick the docker started from step 2 using docker ps + * `text-generation-benchmark -t ` , pass the model-id from docker run command + * after the completion of tests, hit ctrl+c to see the performance data summary. +> Note: This benchmark runs the model with bs=[1, 2, 4, 8, 16, 32], sequence_length=10 and decode_length=8 by default. if you want to run other configs, please check text-generation-benchmark -h and change the parameters. + +### Continuous Batching Benchmark + To run continuous batching benchmark, please refer to [README in examples folder](https://github.com/huggingface/tgi-gaudi/blob/habana-main/examples/README.md). + + ## Adjusting TGI Parameters Maximum sequence length is controlled by two arguments: diff --git a/examples/run_generation.py b/examples/run_generation.py index fedfc259321..a2b43e6fbf4 100644 --- a/examples/run_generation.py +++ b/examples/run_generation.py @@ -31,13 +31,18 @@ def get_args(): parser.add_argument( "--max_concurrent_requests", type=int, default=256, help="Max number of concurrent requests" ) + parser.add_argument( + "--seed", type=int, default=42, help="Random seed for datasets" + ) + return parser.parse_args() def read_dataset( max_input_length: int, total_sample_count: int, - model_id: str + model_id: str, + seed: int, ) -> List[str]: """ Loads public dataset from HF: https://huggingface.co/datasets/DIBT/10k_prompts_ranked @@ -51,7 +56,8 @@ def read_dataset( ) if len(dataset) > total_sample_count: dataset = dataset.select(range(total_sample_count)) - dataset = dataset.shuffle(seed=42) + + dataset = dataset.shuffle(seed=seed) return [sample["prompt"] for sample in dataset] @@ -71,7 +77,7 @@ def is_tgi_available( def main(): args = get_args() dataset = read_dataset( - args.max_input_length, args.total_sample_count, args.model_id + args.max_input_length, args.total_sample_count, args.model_id, args.seed ) if not is_tgi_available(args.server_address): diff --git a/server/poetry.lock b/server/poetry.lock index 64e45765281..1987c3b3148 100644 --- a/server/poetry.lock +++ b/server/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. 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[metadata] lock-version = "2.0" python-versions = ">=3.9,<3.13" -content-hash = "be5965e4e13fed32347983dba1690661f3e59a50d59fa26d4f2a8345418dd5a1" +content-hash = "d169e52a2daaf41488cf7191e3f4ff209d39125941a6d0e656001aae534b1e8d" diff --git a/server/pyproject.toml b/server/pyproject.toml index c1809550f12..46a513117f1 100644 --- a/server/pyproject.toml +++ b/server/pyproject.toml @@ -22,8 +22,8 @@ opentelemetry-instrumentation-grpc = "^0.36b0" hf-transfer = "^0.1.2" sentencepiece = "^0.1.97" peft = "^0.10" -optimum-habana = "1.13.2" -transformers = "4.43.4" +optimum-habana = "1.14.1" +transformers = "4.45.2" numpy = "1.26.4" accelerate = "0.33.0" outlines= { version = "^0.0.36", optional = true } diff --git a/server/requirements.txt b/server/requirements.txt index 0a091a2fe85..d941a894d0d 100644 --- a/server/requirements.txt +++ b/server/requirements.txt @@ -1,40 +1,40 @@ accelerate==0.33.0 ; python_version >= "3.9" and python_version < "3.13" -aiohappyeyeballs==2.4.0 ; python_version >= "3.9" and python_version < "3.13" -aiohttp==3.10.5 ; python_version >= "3.9" and python_version < "3.13" +aiohappyeyeballs==2.4.3 ; python_version >= "3.9" and python_version < "3.13" +aiohttp==3.10.10 ; python_version >= "3.9" and python_version < "3.13" aiosignal==1.3.1 ; python_version >= "3.9" and python_version < "3.13" async-timeout==4.0.3 ; python_version >= "3.9" and python_version < "3.11" attrs==24.2.0 ; python_version >= "3.9" and python_version < "3.13" backoff==2.2.1 ; python_version >= "3.9" and python_version < "3.13" -certifi==2024.7.4 ; python_version >= "3.9" and python_version < "3.13" -charset-normalizer==3.3.2 ; python_version >= "3.9" and python_version < "3.13" +certifi==2024.8.30 ; python_version >= "3.9" and python_version < "3.13" +charset-normalizer==3.4.0 ; python_version >= "3.9" and python_version < "3.13" click==8.1.7 ; python_version >= "3.9" and python_version < "3.13" colorama==0.4.6 ; python_version >= "3.9" and python_version < "3.13" and (sys_platform == "win32" or platform_system == "Windows") coloredlogs==15.0.1 ; python_version >= "3.9" and python_version < "3.13" -datasets==2.21.0 ; python_version >= "3.9" and python_version < "3.13" +datasets==3.0.1 ; python_version >= "3.9" and python_version < "3.13" deprecated==1.2.14 ; python_version >= "3.9" and python_version < "3.13" diffusers==0.29.2 ; python_version >= "3.9" and python_version < "3.13" -dill==0.3.8 ; python_version >= "3.9" and python_version < "3.13" -filelock==3.15.4 ; python_version >= "3.9" and python_version < "3.13" +dill==0.3.7 ; python_version >= "3.9" and python_version < "3.13" +filelock==3.16.1 ; python_version >= "3.9" and python_version < "3.13" frozenlist==1.4.1 ; python_version >= "3.9" and python_version < "3.13" fsspec==2024.6.1 ; python_version >= "3.9" and python_version < "3.13" fsspec[http]==2024.6.1 ; python_version >= "3.9" and python_version < "3.13" -googleapis-common-protos==1.63.2 ; python_version >= "3.9" and python_version < "3.13" +googleapis-common-protos==1.65.0 ; python_version >= "3.9" and python_version < "3.13" grpc-interceptor==0.15.4 ; python_version >= "3.9" and python_version < "3.13" grpcio-reflection==1.48.2 ; python_version >= "3.9" and python_version < "3.13" grpcio-status==1.48.2 ; python_version >= "3.9" and python_version < "3.13" -grpcio==1.66.0 ; python_version >= "3.9" and python_version < "3.13" +grpcio==1.67.0 ; python_version >= "3.9" and python_version < "3.13" hf-transfer==0.1.8 ; python_version >= "3.9" and python_version < "3.13" -huggingface-hub==0.24.6 ; python_version >= "3.9" and python_version < "3.13" +huggingface-hub==0.26.1 ; python_version >= "3.9" and python_version < "3.13" humanfriendly==10.0 ; python_version >= "3.9" and python_version < "3.13" -idna==3.8 ; python_version >= "3.9" and python_version < "3.13" -importlib-metadata==8.4.0 ; python_version >= "3.9" and python_version < "3.13" +idna==3.10 ; python_version >= "3.9" and python_version < "3.13" +importlib-metadata==8.5.0 ; python_version >= "3.9" and python_version < "3.13" jinja2==3.1.4 ; python_version >= "3.9" and python_version < "3.13" joblib==1.4.2 ; python_version >= "3.9" and python_version < "3.13" loguru==0.6.0 ; python_version >= "3.9" and python_version < "3.13" -markupsafe==2.1.5 ; python_version >= "3.9" and python_version < "3.13" +markupsafe==3.0.2 ; python_version >= "3.9" and python_version < "3.13" mpmath==1.3.0 ; python_version >= "3.9" and python_version < "3.13" -multidict==6.0.5 ; python_version >= "3.9" and python_version < "3.13" -multiprocess==0.70.16 ; python_version >= "3.9" and python_version < "3.13" +multidict==6.1.0 ; python_version >= "3.9" and python_version < "3.13" +multiprocess==0.70.15 ; python_version >= "3.9" and python_version < "3.13" networkx==3.2.1 ; python_version >= "3.9" and python_version < "3.13" numpy==1.26.4 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-api==1.15.0 ; python_version >= "3.9" and python_version < "3.13" @@ -46,43 +46,45 @@ opentelemetry-instrumentation==0.36b0 ; python_version >= "3.9" and python_versi opentelemetry-proto==1.15.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-sdk==1.15.0 ; python_version >= "3.9" and python_version < "3.13" opentelemetry-semantic-conventions==0.36b0 ; python_version >= "3.9" and python_version < "3.13" -optimum-habana==1.13.2 ; python_version >= "3.9" and python_version < "3.13" -optimum==1.21.4 ; python_version >= "3.9" and python_version < "3.13" +optimum-habana==1.14.1 ; python_version >= "3.9" and python_version < "3.13" +optimum==1.23.2 ; python_version >= "3.9" and python_version < "3.13" packaging==24.1 ; python_version >= "3.9" and python_version < "3.13" -pandas==2.2.2 ; python_version >= "3.9" and python_version < "3.13" +pandas==2.2.3 ; python_version >= "3.9" and python_version < "3.13" peft==0.10.0 ; python_version >= "3.9" and python_version < "3.13" -pillow==10.4.0 ; python_version >= "3.9" and python_version < "3.13" +pillow==11.0.0 ; python_version >= "3.9" and python_version < "3.13" prometheus-client==0.20.0 ; python_version >= "3.9" and python_version < "3.13" +propcache==0.2.0 ; python_version >= "3.9" and python_version < "3.13" protobuf==3.20.3 ; python_version >= "3.9" and python_version < "3.13" -psutil==6.0.0 ; python_version >= "3.9" and python_version < "3.13" +psutil==6.1.0 ; python_version >= "3.9" and python_version < "3.13" py-cpuinfo==9.0.0 ; python_version >= "3.9" and python_version < "3.13" pyarrow==17.0.0 ; python_version >= "3.9" and python_version < "3.13" -pyreadline3==3.4.1 ; sys_platform == "win32" and python_version >= "3.9" and python_version < "3.13" +pyreadline3==3.5.4 ; sys_platform == "win32" and python_version >= "3.9" and python_version < "3.13" python-dateutil==2.9.0.post0 ; python_version >= "3.9" and python_version < "3.13" -pytz==2024.1 ; python_version >= "3.9" and python_version < "3.13" +pytz==2024.2 ; python_version >= "3.9" and python_version < "3.13" pyyaml==6.0.2 ; python_version >= "3.9" and python_version < "3.13" -regex==2024.7.24 ; python_version >= "3.9" and python_version < "3.13" +regex==2024.9.11 ; python_version >= "3.9" and python_version < "3.13" requests==2.32.3 ; python_version >= "3.9" and python_version < "3.13" -safetensors==0.4.4 ; python_version >= "3.9" and python_version < "3.13" -scikit-learn==1.5.1 ; python_version >= "3.9" and python_version < "3.13" +safetensors==0.4.5 ; python_version >= "3.9" and python_version < "3.13" +scikit-learn==1.5.2 ; python_version >= "3.9" and python_version < "3.13" scipy==1.13.1 ; python_version >= "3.9" and python_version < "3.13" sentence-transformers[train]==3.0.1 ; python_version >= "3.9" and python_version < "3.13" sentencepiece==0.1.99 ; python_version >= "3.9" and python_version < "3.13" -setuptools==73.0.1 ; python_version >= "3.9" and python_version < "3.13" +setuptools==75.2.0 ; python_version >= "3.9" and python_version < "3.13" six==1.16.0 ; python_version >= "3.9" and python_version < "3.13" sympy==1.12.1 ; python_version >= "3.9" and python_version < "3.13" threadpoolctl==3.5.0 ; python_version >= "3.9" and python_version < "3.13" -tokenizers==0.19.1 ; python_version >= "3.9" and python_version < "3.13" +tokenizers==0.20.1 ; python_version >= "3.9" and python_version < "3.13" +torch==2.4.0a0+git74cd574 ; python_version >= "3.9" and python_version < "3.13" tqdm==4.66.5 ; python_version >= "3.9" and python_version < "3.13" -transformers==4.43.4 ; python_version >= "3.9" and python_version < "3.13" -transformers[sentencepiece]==4.43.4 ; python_version >= "3.9" and python_version < "3.13" +transformers==4.45.2 ; python_version >= "3.9" and python_version < "3.13" +transformers[sentencepiece]==4.45.2 ; python_version >= "3.9" and python_version < "3.13" triton==3.0.0 ; platform_system == "Linux" and platform_machine == "x86_64" and python_version < "3.13" and python_version >= "3.9" typer==0.7.0 ; python_version >= "3.9" and python_version < "3.13" typing-extensions==4.12.2 ; python_version >= "3.9" and python_version < "3.13" -tzdata==2024.1 ; python_version >= "3.9" and python_version < "3.13" -urllib3==2.2.2 ; python_version >= "3.9" and python_version < "3.13" +tzdata==2024.2 ; python_version >= "3.9" and python_version < "3.13" +urllib3==2.2.3 ; python_version >= "3.9" and python_version < "3.13" win32-setctime==1.1.0 ; python_version >= "3.9" and python_version < "3.13" and sys_platform == "win32" wrapt==1.16.0 ; python_version >= "3.9" and python_version < "3.13" xxhash==3.5.0 ; python_version >= "3.9" and python_version < "3.13" -yarl==1.9.4 ; python_version >= "3.9" and python_version < "3.13" -zipp==3.20.0 ; python_version >= "3.9" and python_version < "3.13" +yarl==1.16.0 ; python_version >= "3.9" and python_version < "3.13" +zipp==3.20.2 ; python_version >= "3.9" and python_version < "3.13"