← back to Exo
kimi k2 thinking
631cb81009b5ceda32b23b9758039934d39dcbe5 · 2025-11-11 10:03:39 -0800 · Alex Cheema
Files touched
M .github/benchmark-dashboard/index.htmlM .github/configs/bench_simple.yamlM TODO.mdM pyproject.tomlM src/exo/engines/mlx/auto_parallel.pyM src/exo/engines/mlx/utils_mlx.pyM src/exo/master/api.pyM src/exo/shared/models/model_cards.pyM uv.lock
Diff
commit 631cb81009b5ceda32b23b9758039934d39dcbe5
Author: Alex Cheema <41707476+AlexCheema@users.noreply.github.com>
Date: Tue Nov 11 10:03:39 2025 -0800
kimi k2 thinking
---
.github/benchmark-dashboard/index.html | 33 +++++++++++++-
.github/configs/bench_simple.yaml | 79 +++++++++++++++++-----------------
TODO.md | 1 +
pyproject.toml | 1 +
src/exo/engines/mlx/auto_parallel.py | 4 +-
src/exo/engines/mlx/utils_mlx.py | 11 +++--
src/exo/master/api.py | 2 +-
src/exo/shared/models/model_cards.py | 14 ++++++
uv.lock | 40 ++++++++++++++++-
9 files changed, 137 insertions(+), 48 deletions(-)
diff --git a/.github/benchmark-dashboard/index.html b/.github/benchmark-dashboard/index.html
index 5b64af48..5f72a831 100644
--- a/.github/benchmark-dashboard/index.html
+++ b/.github/benchmark-dashboard/index.html
@@ -586,8 +586,37 @@
const modelIds = cluster.model_ids || ['unknown'];
const modelName = modelIds.length === 1 ? modelIds[0] : `${modelIds.length} models`;
- // Get strategy (default to 'N/A' if not specified)
- const strategy = cluster.strategy || 'N/A';
+ // Get strategy (backwards compatible with old format)
+ // New format: sharding + instance_meta, e.g. "Pipeline (MLX Ring)"
+ // Old format: strategy field
+ let strategy = 'N/A';
+ if (cluster.strategy) {
+ // Backwards compatibility: use old strategy field
+ strategy = cluster.strategy;
+ } else if (cluster.sharding || cluster.instance_meta) {
+ // New format: combine sharding and instance_meta
+ const sharding = cluster.sharding || '';
+ const instanceMeta = cluster.instance_meta || '';
+
+ // Format instance_meta: convert camelCase/PascalCase to readable format
+ const formatInstanceMeta = (meta) => {
+ if (!meta) return '';
+ // Insert spaces before capital letters and handle common acronyms
+ return meta
+ .replace(/([A-Z])/g, ' $1')
+ .trim()
+ .replace(/\bMlx\b/g, 'MLX')
+ .replace(/\bIbv\b/g, 'IBV');
+ };
+
+ if (sharding && instanceMeta) {
+ strategy = `${sharding} (${formatInstanceMeta(instanceMeta)})`;
+ } else if (sharding) {
+ strategy = sharding;
+ } else if (instanceMeta) {
+ strategy = formatInstanceMeta(instanceMeta);
+ }
+ }
// For each stage in the configuration, create a row
stages.forEach((stageConfig, stageIdx) => {
diff --git a/.github/configs/bench_simple.yaml b/.github/configs/bench_simple.yaml
index 346df681..91c85020 100644
--- a/.github/configs/bench_simple.yaml
+++ b/.github/configs/bench_simple.yaml
@@ -4,7 +4,7 @@
# Hardware configuration - maps runner labels to instance counts
hardware_plan:
puffin4: 1
- # puffin8: 1
+ puffin8: 1
# Environment variables to set on each node
environment:
@@ -18,14 +18,15 @@ timeout_seconds: 1800
# Model instances to run concurrently
model_ids:
# - "mlx-community/DeepSeek-V3.1-8bit"
- - "mlx-community/Kimi-K2-Instruct-4bit"
+ # - "mlx-community/Kimi-K2-Instruct-4bit"
+ - "mlx-community/Kimi-K2-Thinking"
# - "mlx-community/Qwen3-235B-A22B-4bit"
# - "mlx-community/Llama-3.3-70B-Instruct-4bit"
# - "mlx-community/Llama-3.3-70B-Instruct-8bit"
# - "mlx-community/Llama-3.2-1B-Instruct-4bit"
# Sharding strategy: "Pipeline" or "Tensor"
-sharding: "Tensor"
+sharding: "Pipeline"
# Instance type: "MlxRing" or "MlxIbv"
instance_meta: "MlxIbv"
@@ -46,62 +47,62 @@ stages:
prompt_length: 64
generation_length: 64
time_between_requests: 2.0
- iterations: 10
- - name: "pp64_g512"
- prompt_length: 64
- generation_length: 512
- time_between_requests: 2.0
- iterations: 10
+ iterations: 5
+ # - name: "pp64_g512"
+ # prompt_length: 64
+ # generation_length: 512
+ # time_between_requests: 2.0
+ # iterations: 10
- name: "pp256_g64"
prompt_length: 256
generation_length: 64
time_between_requests: 2.0
- iterations: 10
- - name: "pp256_g512"
- prompt_length: 256
- generation_length: 512
- time_between_requests: 2.0
- iterations: 10
+ iterations: 5
+ # - name: "pp256_g512"
+ # prompt_length: 256
+ # generation_length: 512
+ # time_between_requests: 2.0
+ # iterations: 10
- name: "pp1024_g64"
prompt_length: 1024
generation_length: 64
time_between_requests: 2.0
- iterations: 10
- - name: "pp1024_g512"
- prompt_length: 1024
- generation_length: 512
- time_between_requests: 2.0
- iterations: 10
+ iterations: 5
+ # - name: "pp1024_g512"
+ # prompt_length: 1024
+ # generation_length: 512
+ # time_between_requests: 2.0
+ # iterations: 10
- name: "pp2048_g64"
prompt_length: 2048
generation_length: 64
time_between_requests: 2.0
- iterations: 10
- - name: "pp2048_g512"
- prompt_length: 2048
- generation_length: 512
- time_between_requests: 2.0
- iterations: 10
+ iterations: 5
+ # - name: "pp2048_g512"
+ # prompt_length: 2048
+ # generation_length: 512
+ # time_between_requests: 2.0
+ # iterations: 10
- name: "pp4096_g64"
prompt_length: 4096
generation_length: 64
time_between_requests: 2.0
- iterations: 10
- - name: "pp4096_g512"
- prompt_length: 4096
- generation_length: 512
- time_between_requests: 2.0
- iterations: 10
+ iterations: 5
+ # - name: "pp4096_g512"
+ # prompt_length: 4096
+ # generation_length: 512
+ # time_between_requests: 2.0
+ # iterations: 10
- name: "pp8192_g64"
prompt_length: 8192
generation_length: 64
time_between_requests: 2.0
- iterations: 10
- - name: "pp8192_g512"
- prompt_length: 8192
- generation_length: 512
- time_between_requests: 2.0
- iterations: 10
+ iterations: 5
+ # - name: "pp8192_g512"
+ # prompt_length: 8192
+ # generation_length: 512
+ # time_between_requests: 2.0
+ # iterations: 10
# - name: "pp16384_g64"
# prompt_length: 16384
# generation_length: 64
diff --git a/TODO.md b/TODO.md
index c07c2220..85577411 100644
--- a/TODO.md
+++ b/TODO.md
@@ -19,6 +19,7 @@
21. Make two separate things: tensor or pipeline, and ring or ibv.
22. When downloading for the first time, stuff times out and I think the model never ends up actually loading into memory, or something.
23. Do we need cache_limit? We went back and forth on that a lot because we thought it might be causing issues. One problem is it sets it relative to model size. So if you have multiple models loaded in it will take the most recent model size for the cache_limit. This is problematic if you launch DeepSeek -> Llama for example.
+24. Task cancellation. When API http request gets cancelled, it should cancel corresponding task.
Potential refactors:
diff --git a/pyproject.toml b/pyproject.toml
index 5a7f8fa9..cd617aee 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -36,6 +36,7 @@ dependencies = [
"bidict>=0.23.1",
"mlx>=0.29.3",
"mlx-lm>=0.28.3",
+ "tiktoken>=0.12.0", # required for kimi k2 tokenizer
]
[project.scripts]
diff --git a/src/exo/engines/mlx/auto_parallel.py b/src/exo/engines/mlx/auto_parallel.py
index 3223f86f..452b53c8 100644
--- a/src/exo/engines/mlx/auto_parallel.py
+++ b/src/exo/engines/mlx/auto_parallel.py
@@ -3,7 +3,7 @@ from functools import partial
from inspect import signature
from typing import TYPE_CHECKING, Callable, Protocol, cast, override
-from mlx_lm.models.cache import KVCache
+from mlx_lm.models.cache import KVCache, RotatingKVCache
from mlx_lm.models.deepseek_v3 import DeepseekV3MLP
from mlx_lm.models.deepseek_v3 import Model as DeepseekV3Model
from mlx_lm.models.llama import Model as LlamaModel
@@ -92,7 +92,7 @@ class PipelineLastLayer(CustomMlxLayer):
cache = self.original_layer_signature.bind_partial(x, *args, **kwargs).arguments.get("cache", None)
- assert cache is None or isinstance(cache, KVCache)
+ assert cache is None or isinstance(cache, (KVCache, RotatingKVCache))
output: mx.array = self.original_layer(x, *args, **kwargs)
diff --git a/src/exo/engines/mlx/utils_mlx.py b/src/exo/engines/mlx/utils_mlx.py
index e8e6391b..9e92e723 100644
--- a/src/exo/engines/mlx/utils_mlx.py
+++ b/src/exo/engines/mlx/utils_mlx.py
@@ -2,7 +2,7 @@ import os
import resource
from typing import Any, Callable, cast
-from mlx_lm.models.cache import KVCache
+from mlx_lm.models.cache import KVCache, RotatingKVCache
from mlx_lm.sample_utils import make_sampler
from mlx_lm.tokenizer_utils import TokenizerWrapper
@@ -254,9 +254,14 @@ class NullKVCache(KVCache):
def make_kv_cache(
model: Model,
max_kv_size: int | None = None,
-) -> list[KVCache]:
+) -> list[KVCache | RotatingKVCache]:
assert hasattr(model, "layers")
- return [KVCache() for _ in model.layers]
+ if max_kv_size is None:
+ logger.info("Using default KV cache")
+ return [KVCache() for _ in model.layers]
+ else:
+ logger.info(f"Using rotating KV cache with {max_kv_size=}")
+ return [RotatingKVCache(max_size=max_kv_size) for _ in model.layers]
def mlx_force_oom(size: int = 40000) -> None:
diff --git a/src/exo/master/api.py b/src/exo/master/api.py
index b52dbe29..22074064 100644
--- a/src/exo/master/api.py
+++ b/src/exo/master/api.py
@@ -215,7 +215,7 @@ class API:
while not finished:
# TODO: how long should this timeout be?
chunk = await asyncio.wait_for(
- self._chat_completion_queues[command_id].get(), timeout=60
+ self._chat_completion_queues[command_id].get(), timeout=600
)
assert isinstance(chunk, TokenChunk)
chunk_response: ChatCompletionResponse = chunk_to_response(
diff --git a/src/exo/shared/models/model_cards.py b/src/exo/shared/models/model_cards.py
index 8fc85c48..12051b3b 100644
--- a/src/exo/shared/models/model_cards.py
+++ b/src/exo/shared/models/model_cards.py
@@ -93,6 +93,7 @@ MODEL_CARDS: dict[str, ModelCard] = {
n_layers=61,
),
),
+ # kimi k2
"kimi-k2-instruct-4bit": ModelCard(
short_id="kimi-k2-instruct-4bit",
model_id="mlx-community/Kimi-K2-Instruct-4bit",
@@ -106,6 +107,19 @@ MODEL_CARDS: dict[str, ModelCard] = {
n_layers=61,
),
),
+ "kimi-k2-thinking": ModelCard(
+ short_id="kimi-k2-thinking",
+ model_id="mlx-community/Kimi-K2-Thinking",
+ name="Kimi K2 Thinking",
+ description="""Kimi K2 Thinking is the latest, most capable version of open-source thinking model.""",
+ tags=[],
+ metadata=ModelMetadata(
+ model_id=ModelId("mlx-community/Kimi-K2-Thinking"),
+ pretty_name="Kimi K2 Thinking",
+ storage_size=Memory.from_bytes(577597603840),
+ n_layers=61,
+ ),
+ ),
# llama-3.1
"llama-3.1-8b": ModelCard(
short_id="llama-3.1-8b",
diff --git a/uv.lock b/uv.lock
index 6960924b..a3e25d6f 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,5 +1,5 @@
version = 1
-revision = 3
+revision = 1
requires-python = ">=3.13"
resolution-markers = [
"sys_platform == 'darwin'",
@@ -361,6 +361,7 @@ dependencies = [
{ name = "sqlalchemy", extra = ["asyncio"], marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
{ name = "sqlmodel", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
{ name = "textual", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
+ { name = "tiktoken", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
{ name = "transformers", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
{ name = "typeguard", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
{ name = "types-aiofiles", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
@@ -403,6 +404,7 @@ requires-dist = [
{ name = "sqlalchemy", extras = ["asyncio"], specifier = ">=2.0.43" },
{ name = "sqlmodel", specifier = ">=0.0.24" },
{ name = "textual", specifier = ">=5.3.0" },
+ { name = "tiktoken", specifier = ">=0.12.0" },
{ name = "transformers", specifier = ">=4.55.2" },
{ name = "typeguard", specifier = ">=4.4.4" },
{ name = "types-aiofiles", specifier = ">=24.1.0.20250708" },
@@ -1458,6 +1460,42 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/42/37/1deba011782a49ea249c73adcf703a39b0249ac9b0e17d1a2e4074df8d57/textual-6.5.0-py3-none-any.whl", hash = "sha256:c5505be7fe606b8054fb88431279885f88352bddca64832f6acd293ef7d9b54f", size = 711848, upload-time = "2025-10-31T17:21:51.134Z" },
]
+[[package]]
+name = "tiktoken"
+version = "0.12.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+ { name = "regex", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
+ { name = "requests", marker = "sys_platform == 'darwin' or sys_platform == 'linux'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/7d/ab/4d017d0f76ec3171d469d80fc03dfbb4e48a4bcaddaa831b31d526f05edc/tiktoken-0.12.0.tar.gz", hash = "sha256:b18ba7ee2b093863978fcb14f74b3707cdc8d4d4d3836853ce7ec60772139931", size = 37806 }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/00/61/441588ee21e6b5cdf59d6870f86beb9789e532ee9718c251b391b70c68d6/tiktoken-0.12.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:775c2c55de2310cc1bc9a3ad8826761cbdc87770e586fd7b6da7d4589e13dab3", size = 1050802 },
+ { url = "https://files.pythonhosted.org/packages/1f/05/dcf94486d5c5c8d34496abe271ac76c5b785507c8eae71b3708f1ad9b45a/tiktoken-0.12.0-cp313-cp313-macosx_11_0_arm64.whl", hash = "sha256:a01b12f69052fbe4b080a2cfb867c4de12c704b56178edf1d1d7b273561db160", size = 993995 },
+ { url = "https://files.pythonhosted.org/packages/a0/70/5163fe5359b943f8db9946b62f19be2305de8c3d78a16f629d4165e2f40e/tiktoken-0.12.0-cp313-cp313-manylinux_2_28_aarch64.whl", hash = "sha256:01d99484dc93b129cd0964f9d34eee953f2737301f18b3c7257bf368d7615baa", size = 1128948 },
+ { url = "https://files.pythonhosted.org/packages/0c/da/c028aa0babf77315e1cef357d4d768800c5f8a6de04d0eac0f377cb619fa/tiktoken-0.12.0-cp313-cp313-manylinux_2_28_x86_64.whl", hash = "sha256:4a1a4fcd021f022bfc81904a911d3df0f6543b9e7627b51411da75ff2fe7a1be", size = 1151986 },
+ { url = "https://files.pythonhosted.org/packages/a0/5a/886b108b766aa53e295f7216b509be95eb7d60b166049ce2c58416b25f2a/tiktoken-0.12.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:981a81e39812d57031efdc9ec59fa32b2a5a5524d20d4776574c4b4bd2e9014a", size = 1194222 },
+ { url = "https://files.pythonhosted.org/packages/f4/f8/4db272048397636ac7a078d22773dd2795b1becee7bc4922fe6207288d57/tiktoken-0.12.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:9baf52f84a3f42eef3ff4e754a0db79a13a27921b457ca9832cf944c6be4f8f3", size = 1255097 },
+ { url = "https://files.pythonhosted.org/packages/ce/76/994fc868f88e016e6d05b0da5ac24582a14c47893f4474c3e9744283f1d5/tiktoken-0.12.0-cp313-cp313t-macosx_10_13_x86_64.whl", hash = "sha256:d5f89ea5680066b68bcb797ae85219c72916c922ef0fcdd3480c7d2315ffff16", size = 1050309 },
+ { url = "https://files.pythonhosted.org/packages/f6/b8/57ef1456504c43a849821920d582a738a461b76a047f352f18c0b26c6516/tiktoken-0.12.0-cp313-cp313t-macosx_11_0_arm64.whl", hash = "sha256:b4e7ed1c6a7a8a60a3230965bdedba8cc58f68926b835e519341413370e0399a", size = 993712 },
+ { url = "https://files.pythonhosted.org/packages/72/90/13da56f664286ffbae9dbcfadcc625439142675845baa62715e49b87b68b/tiktoken-0.12.0-cp313-cp313t-manylinux_2_28_aarch64.whl", hash = "sha256:fc530a28591a2d74bce821d10b418b26a094bf33839e69042a6e86ddb7a7fb27", size = 1128725 },
+ { url = "https://files.pythonhosted.org/packages/05/df/4f80030d44682235bdaecd7346c90f67ae87ec8f3df4a3442cb53834f7e4/tiktoken-0.12.0-cp313-cp313t-manylinux_2_28_x86_64.whl", hash = "sha256:06a9f4f49884139013b138920a4c393aa6556b2f8f536345f11819389c703ebb", size = 1151875 },
+ { url = "https://files.pythonhosted.org/packages/22/1f/ae535223a8c4ef4c0c1192e3f9b82da660be9eb66b9279e95c99288e9dab/tiktoken-0.12.0-cp313-cp313t-musllinux_1_2_aarch64.whl", hash = "sha256:04f0e6a985d95913cabc96a741c5ffec525a2c72e9df086ff17ebe35985c800e", size = 1194451 },
+ { url = "https://files.pythonhosted.org/packages/78/a7/f8ead382fce0243cb625c4f266e66c27f65ae65ee9e77f59ea1653b6d730/tiktoken-0.12.0-cp313-cp313t-musllinux_1_2_x86_64.whl", hash = "sha256:0ee8f9ae00c41770b5f9b0bb1235474768884ae157de3beb5439ca0fd70f3e25", size = 1253794 },
+ { url = "https://files.pythonhosted.org/packages/72/05/3abc1db5d2c9aadc4d2c76fa5640134e475e58d9fbb82b5c535dc0de9b01/tiktoken-0.12.0-cp314-cp314-macosx_10_13_x86_64.whl", hash = "sha256:a90388128df3b3abeb2bfd1895b0681412a8d7dc644142519e6f0a97c2111646", size = 1050188 },
+ { url = "https://files.pythonhosted.org/packages/e3/7b/50c2f060412202d6c95f32b20755c7a6273543b125c0985d6fa9465105af/tiktoken-0.12.0-cp314-cp314-macosx_11_0_arm64.whl", hash = "sha256:da900aa0ad52247d8794e307d6446bd3cdea8e192769b56276695d34d2c9aa88", size = 993978 },
+ { url = "https://files.pythonhosted.org/packages/14/27/bf795595a2b897e271771cd31cb847d479073497344c637966bdf2853da1/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_aarch64.whl", hash = "sha256:285ba9d73ea0d6171e7f9407039a290ca77efcdb026be7769dccc01d2c8d7fff", size = 1129271 },
+ { url = "https://files.pythonhosted.org/packages/f5/de/9341a6d7a8f1b448573bbf3425fa57669ac58258a667eb48a25dfe916d70/tiktoken-0.12.0-cp314-cp314-manylinux_2_28_x86_64.whl", hash = "sha256:d186a5c60c6a0213f04a7a802264083dea1bbde92a2d4c7069e1a56630aef830", size = 1151216 },
+ { url = "https://files.pythonhosted.org/packages/75/0d/881866647b8d1be4d67cb24e50d0c26f9f807f994aa1510cb9ba2fe5f612/tiktoken-0.12.0-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:604831189bd05480f2b885ecd2d1986dc7686f609de48208ebbbddeea071fc0b", size = 1194860 },
+ { url = "https://files.pythonhosted.org/packages/b3/1e/b651ec3059474dab649b8d5b69f5c65cd8fcd8918568c1935bd4136c9392/tiktoken-0.12.0-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:8f317e8530bb3a222547b85a58583238c8f74fd7a7408305f9f63246d1a0958b", size = 1254567 },
+ { url = "https://files.pythonhosted.org/packages/ac/a4/72eed53e8976a099539cdd5eb36f241987212c29629d0a52c305173e0a68/tiktoken-0.12.0-cp314-cp314t-macosx_10_13_x86_64.whl", hash = "sha256:c2c714c72bc00a38ca969dae79e8266ddec999c7ceccd603cc4f0d04ccd76365", size = 1050473 },
+ { url = "https://files.pythonhosted.org/packages/e6/d7/0110b8f54c008466b19672c615f2168896b83706a6611ba6e47313dbc6e9/tiktoken-0.12.0-cp314-cp314t-macosx_11_0_arm64.whl", hash = "sha256:cbb9a3ba275165a2cb0f9a83f5d7025afe6b9d0ab01a22b50f0e74fee2ad253e", size = 993855 },
+ { url = "https://files.pythonhosted.org/packages/5f/77/4f268c41a3957c418b084dd576ea2fad2e95da0d8e1ab705372892c2ca22/tiktoken-0.12.0-cp314-cp314t-manylinux_2_28_aarch64.whl", hash = "sha256:dfdfaa5ffff8993a3af94d1125870b1d27aed7cb97aa7eb8c1cefdbc87dbee63", size = 1129022 },
+ { url = "https://files.pythonhosted.org/packages/4e/2b/fc46c90fe5028bd094cd6ee25a7db321cb91d45dc87531e2bdbb26b4867a/tiktoken-0.12.0-cp314-cp314t-manylinux_2_28_x86_64.whl", hash = "sha256:584c3ad3d0c74f5269906eb8a659c8bfc6144a52895d9261cdaf90a0ae5f4de0", size = 1150736 },
+ { url = "https://files.pythonhosted.org/packages/28/c0/3c7a39ff68022ddfd7d93f3337ad90389a342f761c4d71de99a3ccc57857/tiktoken-0.12.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:54c891b416a0e36b8e2045b12b33dd66fb34a4fe7965565f1b482da50da3e86a", size = 1194908 },
+ { url = "https://files.pythonhosted.org/packages/ab/0d/c1ad6f4016a3968c048545f5d9b8ffebf577774b2ede3e2e352553b685fe/tiktoken-0.12.0-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:5edb8743b88d5be814b1a8a8854494719080c28faaa1ccbef02e87354fe71ef0", size = 1253706 },
+]
+
[[package]]
name = "tokenizers"
version = "0.22.1"
← 364087b9 five billion percent better shutdown handling
·
back to Exo
·
improved master error handling b62f6847 →