Skip to main content

bithuman

Run a bitHuman avatar on your own machine, in your own process.

pip install bithuman
DEMO=$(python -c 'import bithuman,os; print(os.path.join(os.path.dirname(bithuman.__file__), "assets", "demo_sample.wav"))')
python -m bithuman render sofia-ramirez "$DEMO"     # -> sofia-ramirez.mp4

Two arguments — an avatar and some audio — and a video you can play (with your API secret in BITHUMAN_API_SECRET; see the key). The avatar is a showcase name (python -m bithuman list), your agent's ten-character code (python -m bithuman list --mine; fetched once, which is free), or a file you already have. The audio above is 15 s of speech that ships with this package, so the first run needs nothing you do not already have. It is the same command line as the bithuman CLI: render <avatar> <audio> [-o out.mp4] [--limit N] [--json], list [--mine], and one sign-in (bithuman login) serves both.

In your own program it is the same two things. The command above fetched the avatar to ~/.cache/bithuman/showcase/:

import bithuman, os

speech = os.path.join(os.path.dirname(bithuman.__file__),
                      "assets", "demo_sample.wav")   # 15 s, ships in the wheel
avatar_file = os.path.expanduser("~/.cache/bithuman/showcase/sofia-ramirez.imx")

avatar = bithuman.open(avatar_file)
frames = 0
for image in avatar.render(speech):   # each image: (height, width, 3) uint8, RGB
    frames += 1
print(frames, "frames")

That is the whole thing: open an avatar, then render audio through it.

both families, the same two lines

An essence-2 avatar and an expression-2 avatar are opened and rendered by the code above, unchanged. Nothing you write says which one you have, and you do not have to know.

expression-2 needs one extra package on the machine:

pip install "bithuman[expression-2]"

Open an expression-2 avatar without it and the refusal says so, and says that line. Nothing else differs.

offline rendering, without 3 GB of CUDA you will never run

bithuman[offline] adds torch and onnxruntime. From PyPI's default index that resolves to the CUDA build of torch, and the extra costs 3.18 GB of wheels — 2.45 GB of it nvidia-*, cuda-* and triton that the offline route never executes. Install torch first from PyTorch's own selector — choose the Compute Platform without CUDA and run the one line it prints — and the same extra then resolves to 0.18 GB, with no CUDA wheel in the set at all (the extra asks for torch>=2.1, and any build satisfies it):

pip install "bithuman[offline]"      # after torch, from the line the selector printed

(Measured 2026-09-19 on Linux x86_64 with pip install --dry-run --report: 49 wheels / 3.18 GB from the default index alone, 30 wheels / 0.18 GB with PyTorch's CUDA-free index beside it. Use the default index only if you actually want CUDA.)


The surface — eight names

you write it means
bithuman.open(source) open the avatar file on this machine; returns an Avatar
avatar.render(audio) yield the frames for that audio
Avatar what open gives you
AvatarError catch this for any refusal
InvalidAvatar we cannot find it, or it is not a usable avatar
NotSupported this avatar cannot run here
NotAuthorised the key is missing, invalid, or out of credit
Failed we could not do it — the message says which

There is nothing else, and nothing to configure. This package runs the avatar on this machine, so there is no choice left about where or how it runs.

audio in

audio is 16 kHz mono, and it is either a buffer or a stream — the same call:

avatar.render(speech)                      # an audio file path
avatar.render(samples)                     # int16 or float32 in [-1, 1]
avatar.render(raw_bytes)                   # 16 kHz mono, signed 16-bit
avatar.render(microphone())                # any iterable of the above

frames out

Each frame is a (height, width, 3) uint8 array in RGB order, in order, at the avatar's own frame rate — which is a property of the avatar, not something to choose. (This line read "one per 40 ms of speech" until 2026-09-06, which was true of every avatar the package could open at the time and is not true of an expression-2 one.)

import cv2
for image in avatar.render(speech):
    cv2.imshow("avatar", image[:, :, ::-1])   # OpenCV wants BGR
    cv2.waitKey(1)

stopping early

Someone interrupting the avatar is "stop consuming and close the iterator":

images = avatar.render(speech)
for n, image in enumerate(images):
    if n == 50:                       # e.g. the user started talking
        images.close()
        break

releasing it

with frees everything at the end of the block; without it, the avatar is freed when it is garbage collected.

with bithuman.open(avatar_file) as avatar:
    for image in avatar.render(speech):
        frames += 1

The four refusals

Each one leads to a different fix, and none of them asks you to know anything about how we are built.

try:
    avatar = bithuman.open(avatar_file)
    for image in avatar.render(speech):
        pass
except bithuman.InvalidAvatar:
    ...   # fix the path or the code, or fetch the avatar again
except bithuman.NotSupported:
    ...   # use the cloud package, or another device
except bithuman.NotAuthorised:
    ...   # fix the credential
except bithuman.Failed:
    ...   # retry, then report it

Every one of them is an AvatarError, so except bithuman.AvatarError catches all four.


The key

Rendering is metered, and the key belongs in the environment rather than in your code:

export BITHUMAN_API_SECRET=...

Without one, render refuses with NotAuthorised before it hands you a frame. Get a key at https://www.bithuman.ai/developer/api-keys.

python -m bithuman also reads a .env file beside you, which is where a key usually already is. What is already in the environment always wins.


Where it runs

Python 3.10 – 3.14
macOS Apple silicon
Linux x86-64 and arm64
Windows, Intel Macs not built — pip install refuses loudly rather than quietly giving you an old release

ffmpeg is used to read an audio file when it is on your PATH; when it is not, the decoder this package already installs reads the same file in this process, so it is not something to install first.

Two environment variables:

BITHUMAN_API_SECRET your API secret, from https://www.bithuman.ai/developer/api-keys — rendering is metered, so it is required unless you pass api_secret=. BITHUMAN_API_KEY is read as a deprecated alias
BITHUMAN_CACHE_DIR where a prepared avatar is kept (default ~/.cache/bithuman)

This package never puts a command on your PATH

pip install bithuman installs a library and nothing else — and python -m bithuman is why that costs you nothing: a module needs no script, cannot collide with one, and is there the moment pip finishes. The full bithuman command-line tool (a live avatar, a conversation) is a different artifact and is not installed with pip:

curl -fsSL https://raw.githubusercontent.com/bithuman-product/homebrew-bithuman/main/install.sh | sh
brew install bithuman-product/bithuman/bithuman-cli      # macOS, equivalently

That is an invariant, not an accident: a pip-installed command named bithuman would overwrite the one Homebrew put at the same path, and every check would still report success. tests/test_no_console_script.py fails if a release ever grows one — on every push and pull request (the source side, with three firing controls) and again inside each publish job, run directly against the wheels being uploaded. A directory that is declared and holds no bithuman wheel exits 2: a publish that cannot be graded is refused, not passed.


Using it from a LiveKit agent

The LiveKit integration is a separate package, livekit-plugins-bithuman, published by LiveKit out of github.com/livekit/agents. Install pillow beside it:

pip install livekit-plugins-bithuman pillow

That plugin imports PIL.Image at module scope and its published metadata does not declare pillow, so installing it on its own ends at ModuleNotFoundError: No module named 'PIL' the first time you import it. The metadata is upstream's, not ours — this line is the whole fix, and the deploy guide carries it too.

On Python 3.10 and 3.14 there is a second one, and pillow alone does not clear it. That plugin declares bithuman behind a python_version >= "3.11" and python_version < "3.14" marker, so on those two interpreters pip reports success and installs no bithuman at all — which takes cv2 with it, and the import dies there instead. This package publishes cp310 and cp314 wheels that install and import cleanly, so name it yourself:

pip install livekit-plugins-bithuman pillow bithuman     # Python 3.10 / 3.14

Both workarounds have an expiry: pillow and the dropped marker are already merged upstream in livekit/agents#7280 and are waiting on a plugin release. A release after that commit needs neither word.

Coming from 2.10.0?

3.0.0 is a clean break. Thirty-two names became eight, and fourteen error classes became four.

if you see do this
cannot import name 'AsyncBithuman' (or Bithuman, AudioChunk, VideoFrame, VideoControl) bithuman.open(...) and avatar.render(audio) replace all of them
cannot import name 'Fixture' (or Runtime, EP_AUTO, ComposedFrame) same: they were the layer under render, and there is no layer to reach for now
no module named 'bithuman.api' (or .models, .exceptions, .config, .bhci) the values they held are gone from the surface; the four refusals replace the error classes
a DeprecationWarning when you import the 2.x offline-render module it still works until 4.0.0; the warning names the module and the class names to write instead (bithuman.offline, OfflineRenderer, OfflineRenderError)
module 'bithuman' has no attribute '__version__' importlib.metadata.version("bithuman")
you install the 2.x extra for offline rendering it still installs the same three packages until 4.0.0; the extra is now bithuman[offline]
your frames look blue frames are RGB now, not BGR — image[:, :, ::-1] if you feed OpenCV
except BithumanError never fires except bithuman.AvatarError

Frames are still (height, width, 3) uint8 arrays, still 25 per second, still in order.

2.10.0 is on PyPI forever and keeps resolving exactly as it does today. Pin bithuman<3 to stay on it.


Licence

Proprietary — this package carries the runtime. See LICENSE.

Metadata

Release files for bithuman 2.11.18

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for bithuman 2.11.18
File Size Uploaded
bithuman-2.11.18.tar.gz 2.1 kB Details

Built distributions (wheels)

Table of built distributions (wheels) for bithuman 2.11.18
File
bithuman-2.11.18-cp314-cp314-win_amd64.whl CPython 3.14 CPython 3.14 Windows x86-64 Details
bithuman-2.11.18-cp314-cp314-manylinux_2_28_x86_64.whl CPython 3.14 CPython 3.14 Linux glibc 2.28+ x86-64 Details
bithuman-2.11.18-cp314-cp314-manylinux_2_28_aarch64.whl CPython 3.14 CPython 3.14 Linux glibc 2.28+ ARM64 Details
bithuman-2.11.18-cp314-cp314-macosx_14_0_arm64.whl CPython 3.14 CPython 3.14 macOS 14.0+ ARM64 Details
bithuman-2.11.18-cp313-cp313-win_amd64.whl CPython 3.13 CPython 3.13 Windows x86-64 Details
bithuman-2.11.18-cp313-cp313-manylinux_2_28_x86_64.whl CPython 3.13 CPython 3.13 Linux glibc 2.28+ x86-64 Details
bithuman-2.11.18-cp313-cp313-manylinux_2_28_aarch64.whl CPython 3.13 CPython 3.13 Linux glibc 2.28+ ARM64 Details
bithuman-2.11.18-cp313-cp313-macosx_14_0_arm64.whl CPython 3.13 CPython 3.13 macOS 14.0+ ARM64 Details
bithuman-2.11.18-cp312-cp312-win_amd64.whl CPython 3.12 CPython 3.12 Windows x86-64 Details
bithuman-2.11.18-cp312-cp312-manylinux_2_28_x86_64.whl CPython 3.12 CPython 3.12 Linux glibc 2.28+ x86-64 Details
bithuman-2.11.18-cp312-cp312-manylinux_2_28_aarch64.whl CPython 3.12 CPython 3.12 Linux glibc 2.28+ ARM64 Details
bithuman-2.11.18-cp312-cp312-macosx_14_0_arm64.whl CPython 3.12 CPython 3.12 macOS 14.0+ ARM64 Details
bithuman-2.11.18-cp311-cp311-win_amd64.whl CPython 3.11 CPython 3.11 Windows x86-64 Details
bithuman-2.11.18-cp311-cp311-manylinux_2_28_x86_64.whl CPython 3.11 CPython 3.11 Linux glibc 2.28+ x86-64 Details
bithuman-2.11.18-cp311-cp311-manylinux_2_28_aarch64.whl CPython 3.11 CPython 3.11 Linux glibc 2.28+ ARM64 Details
bithuman-2.11.18-cp311-cp311-macosx_14_0_arm64.whl CPython 3.11 CPython 3.11 macOS 14.0+ ARM64 Details
bithuman-2.11.18-cp310-cp310-win_amd64.whl CPython 3.10 CPython 3.10 Windows x86-64 Details
bithuman-2.11.18-cp310-cp310-manylinux_2_28_x86_64.whl CPython 3.10 CPython 3.10 Linux glibc 2.28+ x86-64 Details
bithuman-2.11.18-cp310-cp310-manylinux_2_28_aarch64.whl CPython 3.10 CPython 3.10 Linux glibc 2.28+ ARM64 Details
bithuman-2.11.18-cp310-cp310-macosx_14_0_arm64.whl CPython 3.10 CPython 3.10 macOS 14.0+ ARM64 Details

Total release size: 446.1 MB

Release files / bithuman-2.11.18.tar.gz

Download URL bithuman-2.11.18.tar.gz
Size 2.1 kB
Tags Source
SHA-256 checksum
How to use checksums
f9fb052e7f493431068394a563539074826d9fd87d7ac67f618442309ee64a5d
BLAKE2b-256 checksum
How to use checksums
d25f330b8558c7f447146a032bcc243557a2b6545963d38ae715eaa0ad7035e3
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp314-cp314-win_amd64.whl

Download URL bithuman-2.11.18-cp314-cp314-win_amd64.whl
Size 13.4 MB
Tags CPython 3.14 Windows x86-64
SHA-256 checksum
How to use checksums
05c2ec01a7a6bee50c431575347544542d3afeffe69325e5b6562d891753a0b5
BLAKE2b-256 checksum
How to use checksums
db36e5605cdb762f2c225488e7078a5f236516a4f2dfbbfdc30e9c6fa600e038
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp314-cp314-manylinux_2_28_x86_64.whl

Download URL bithuman-2.11.18-cp314-cp314-manylinux_2_28_x86_64.whl
Size 22.9 MB
Tags CPython 3.14 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
c8c951a1764652e9d05dc4a005028819219540d964387883cc3e72ec3bca3c73
BLAKE2b-256 checksum
How to use checksums
e4c236da7902fcd63da6a4967f8d31d0b19491197076dc632773fc4c8b3df9e8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp314-cp314-manylinux_2_28_aarch64.whl

Download URL bithuman-2.11.18-cp314-cp314-manylinux_2_28_aarch64.whl
Size 21.2 MB
Tags CPython 3.14 Linux glibc 2.28+ ARM64
SHA-256 checksum
How to use checksums
880b802a3da3f43d03f5de3cde0ef59edf3dc8c28d941d71877987bb967ee3a5
BLAKE2b-256 checksum
How to use checksums
2fef294cb757320936df95df68b642a8968b8cb82673b10f876cefe9de5c8c8a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp314-cp314-macosx_14_0_arm64.whl

Download URL bithuman-2.11.18-cp314-cp314-macosx_14_0_arm64.whl
Size 32.0 MB
Tags CPython 3.14 macOS 14.0+ ARM64
SHA-256 checksum
How to use checksums
f7b84a932f67a33c3a227ef9276bacd154d39d600281b1663e6a69d8af6d5110
BLAKE2b-256 checksum
How to use checksums
e1d88182454be255291a7f167ebde5b84f32c8198af5a4e85a2beed44161aff9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp313-cp313-win_amd64.whl

Download URL bithuman-2.11.18-cp313-cp313-win_amd64.whl
Size 13.1 MB
Tags CPython 3.13 Windows x86-64
SHA-256 checksum
How to use checksums
ac3fc3e4b1c28196bd886eb4edfda364fede2f941b188b909b92f8f0b3eac413
BLAKE2b-256 checksum
How to use checksums
dc0d6181f884bb86f79fd1be45768a234282bb6407f834dcee21dff0d3ded139
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp313-cp313-manylinux_2_28_x86_64.whl

Download URL bithuman-2.11.18-cp313-cp313-manylinux_2_28_x86_64.whl
Size 22.9 MB
Tags CPython 3.13 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
7b067cbdedd9a6c26df7a242d941a4a9e024d971433366b7a0f4ff011810c264
BLAKE2b-256 checksum
How to use checksums
ff3cbc7108e12513dfadcc9d9bce2f1305860979505d9315be0539d44c2a7bb7
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp313-cp313-manylinux_2_28_aarch64.whl

Download URL bithuman-2.11.18-cp313-cp313-manylinux_2_28_aarch64.whl
Size 21.2 MB
Tags CPython 3.13 Linux glibc 2.28+ ARM64
SHA-256 checksum
How to use checksums
7ff6364a3f8f21449066616fca523c413ba85afa6b1786369e4739a875513c16
BLAKE2b-256 checksum
How to use checksums
86ec001193896581d2b92222127b9e9db4e1f61ace0fbbe1e5d31d7c26520c8a
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp313-cp313-macosx_14_0_arm64.whl

Download URL bithuman-2.11.18-cp313-cp313-macosx_14_0_arm64.whl
Size 32.0 MB
Tags CPython 3.13 macOS 14.0+ ARM64
SHA-256 checksum
How to use checksums
b69aad171f1cfa48a66eb02d955e5da28ac25ace1b0d66bc97ae3bf5c87b3a0f
BLAKE2b-256 checksum
How to use checksums
11d134db0d25f457a9496c488332f6dcf4468ff92336679fed5b381e0f94bdaf
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp312-cp312-win_amd64.whl

Download URL bithuman-2.11.18-cp312-cp312-win_amd64.whl
Size 13.1 MB
Tags CPython 3.12 Windows x86-64
SHA-256 checksum
How to use checksums
05fa3fd6a3c17652196b59e6909abe1f0a72b2f861c7b91843001868a003a255
BLAKE2b-256 checksum
How to use checksums
5579f1a5a4f474fd9b89316dab7127b5d66641ad405d838e53b7d7d38f40cc2c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp312-cp312-manylinux_2_28_x86_64.whl

Download URL bithuman-2.11.18-cp312-cp312-manylinux_2_28_x86_64.whl
Size 22.9 MB
Tags CPython 3.12 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
9c614160b97cb93b891582f083f6002687213676d6b56e29a27cd37b0b4bbd93
BLAKE2b-256 checksum
How to use checksums
7642bcecc97a0733322696a7093e2d73926faddbaf157e91410defec06c30016
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp312-cp312-manylinux_2_28_aarch64.whl

Download URL bithuman-2.11.18-cp312-cp312-manylinux_2_28_aarch64.whl
Size 21.2 MB
Tags CPython 3.12 Linux glibc 2.28+ ARM64
SHA-256 checksum
How to use checksums
d0dac2bf7949477a5852fb0f36253f356e61284990bba36e069407516c57f04b
BLAKE2b-256 checksum
How to use checksums
eeccedabfb091ca8112462bd08915a3cef05b6e3535fc59096ad9dfabb7ffdc0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp312-cp312-macosx_14_0_arm64.whl

Download URL bithuman-2.11.18-cp312-cp312-macosx_14_0_arm64.whl
Size 32.0 MB
Tags CPython 3.12 macOS 14.0+ ARM64
SHA-256 checksum
How to use checksums
9ad6c840955b0765de3073dfeb119c93b13767788683d578907f58087be727aa
BLAKE2b-256 checksum
How to use checksums
33fc8ddce0e257c67e139b46711eeb58243b0d6f0f67a991a13ef05203a50f2b
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp311-cp311-win_amd64.whl

Download URL bithuman-2.11.18-cp311-cp311-win_amd64.whl
Size 13.1 MB
Tags CPython 3.11 Windows x86-64
SHA-256 checksum
How to use checksums
a05c8ef0864fa4dc07447b4999748cf54bbd6d9b06d4ef89480f129d81aed48b
BLAKE2b-256 checksum
How to use checksums
9588f6a6030d4e87c230cad72d122d28b8a3dad3d7022aa94b76aff47de70d44
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp311-cp311-manylinux_2_28_x86_64.whl

Download URL bithuman-2.11.18-cp311-cp311-manylinux_2_28_x86_64.whl
Size 22.9 MB
Tags CPython 3.11 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
3f78bc26da156a97274211467e4c2a128d8acd230e5617e0d8f58daf8fbf2eeb
BLAKE2b-256 checksum
How to use checksums
c86fa21d0b8e5c0d3c08de9773771fbbea74a630f8a274b8f225ebfb309c762c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp311-cp311-manylinux_2_28_aarch64.whl

Download URL bithuman-2.11.18-cp311-cp311-manylinux_2_28_aarch64.whl
Size 21.2 MB
Tags CPython 3.11 Linux glibc 2.28+ ARM64
SHA-256 checksum
How to use checksums
75c80c29dc25e45aa80c2db6e991e99678d561cd6d2a2a7bd7a2a40dc4b0db8a
BLAKE2b-256 checksum
How to use checksums
adbaf130a0c7ea296346501f30e008c01b1615b7043823ca6ec558a4b3efe527
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp311-cp311-macosx_14_0_arm64.whl

Download URL bithuman-2.11.18-cp311-cp311-macosx_14_0_arm64.whl
Size 32.0 MB
Tags CPython 3.11 macOS 14.0+ ARM64
SHA-256 checksum
How to use checksums
b74a73c7039e7490ab516630feabade2ae3207933890504c97891226f968f4ed
BLAKE2b-256 checksum
How to use checksums
64d0ebbe7ad8fe4de32c18760a79dd283c0f2f3e6db843d3ca54a952d9dfe46f
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp310-cp310-win_amd64.whl

Download URL bithuman-2.11.18-cp310-cp310-win_amd64.whl
Size 13.1 MB
Tags CPython 3.10 Windows x86-64
SHA-256 checksum
How to use checksums
8a9ba329aafc1f5a241e6df641b3340e5bf5d4cf2077a428e853e8e5a0b36bf6
BLAKE2b-256 checksum
How to use checksums
382928618f12dc468ac5eea01161cd8fdeabdae9a250f5fcd3757dd71f06c910
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp310-cp310-manylinux_2_28_x86_64.whl

Download URL bithuman-2.11.18-cp310-cp310-manylinux_2_28_x86_64.whl
Size 22.9 MB
Tags CPython 3.10 Linux glibc 2.28+ x86-64
SHA-256 checksum
How to use checksums
b96596353a2eb89f996c4da82a74628ad0e19fe686224f71518781d72b547d36
BLAKE2b-256 checksum
How to use checksums
f1102cc2329f0f877b99f2c3f5791f33a77c4873324bd250ae91fcdfe764bd44
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp310-cp310-manylinux_2_28_aarch64.whl

Download URL bithuman-2.11.18-cp310-cp310-manylinux_2_28_aarch64.whl
Size 21.2 MB
Tags CPython 3.10 Linux glibc 2.28+ ARM64
SHA-256 checksum
How to use checksums
d7fad91ae94e94a9d0967518f03bf68ecb3f20b6006f42d21afd44945b16e21e
BLAKE2b-256 checksum
How to use checksums
ac1c799c29159614a2ab4b7afa247d22864bd5f02c9d5fc319d4f4a5ac0fc7af
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release files / bithuman-2.11.18-cp310-cp310-macosx_14_0_arm64.whl

Download URL bithuman-2.11.18-cp310-cp310-macosx_14_0_arm64.whl
Size 32.0 MB
Tags CPython 3.10 macOS 14.0+ ARM64
SHA-256 checksum
How to use checksums
a0cd8f3776af58ebee8fafb2e86628733182ca5f252700a1c394881dbfd35c9e
BLAKE2b-256 checksum
How to use checksums
7b33ff427ea5250d0d8dbfeab2c8e0dd68212a2d05a3ae16a596de534bdf7d32
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/7.0.0 CPython/3.12.13

Release history Release notifications | RSS feed

This release

2.11.18 This release

21 release files

2.3.4

15 release files

1.15.2

3 release files

1.15.1

3 release files

1.15.0

3 release files

1.14.0

3 release files

1.13.0

3 release files

1.12.4

3 release files

1.12.3

3 release files

1.12.2

3 release files

1.12.1

3 release files

1.12.0

3 release files

0.8.1

24 release files

0.1.3

3 release files

0.1.2

1 release file

0.1.1

1 release file

0.1.0

1 release file

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page