Querent-ai / querent-python-research

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Bump the pip group with 2 updates #309

Closed dependabot[bot] closed 5 months ago

dependabot[bot] commented 5 months ago

Bumps the pip group with 2 updates: requests and transformers.

Updates requests from 2.31.0 to 2.32.0

Release notes

Sourced from requests's releases.

v2.32.0

2.32.0 (2024-05-20)

🐍 PYCON US 2024 EDITION 🐍

Security

Improvements

  • verify=True now reuses a global SSLContext which should improve request time variance between first and subsequent requests. It should also minimize certificate load time on Windows systems when using a Python version built with OpenSSL 3.x. (#6667)
  • Requests now supports optional use of character detection (chardet or charset_normalizer) when repackaged or vendored. This enables pip and other projects to minimize their vendoring surface area. The Response.text() and apparent_encoding APIs will default to utf-8 if neither library is present. (#6702)

Bugfixes

  • Fixed bug in length detection where emoji length was incorrectly calculated in the request content-length. (#6589)
  • Fixed deserialization bug in JSONDecodeError. (#6629)
  • Fixed bug where an extra leading / (path separator) could lead urllib3 to unnecessarily reparse the request URI. (#6644)

Deprecations

  • Requests has officially added support for CPython 3.12 (#6503)
  • Requests has officially added support for PyPy 3.9 and 3.10 (#6641)
  • Requests has officially dropped support for CPython 3.7 (#6642)
  • Requests has officially dropped support for PyPy 3.7 and 3.8 (#6641)

Documentation

  • Various typo fixes and doc improvements.

Packaging

  • Requests has started adopting some modern packaging practices. The source files for the projects (formerly requests) is now located in src/requests in the Requests sdist. (#6506)
  • Starting in Requests 2.33.0, Requests will migrate to a PEP 517 build system using hatchling. This should not impact the average user, but extremely old versions of packaging utilities may have issues with the new packaging format.

New Contributors

... (truncated)

Changelog

Sourced from requests's changelog.

2.32.0 (2024-05-20)

Security

Improvements

  • verify=True now reuses a global SSLContext which should improve request time variance between first and subsequent requests. It should also minimize certificate load time on Windows systems when using a Python version built with OpenSSL 3.x. (#6667)
  • Requests now supports optional use of character detection (chardet or charset_normalizer) when repackaged or vendored. This enables pip and other projects to minimize their vendoring surface area. The Response.text() and apparent_encoding APIs will default to utf-8 if neither library is present. (#6702)

Bugfixes

  • Fixed bug in length detection where emoji length was incorrectly calculated in the request content-length. (#6589)
  • Fixed deserialization bug in JSONDecodeError. (#6629)
  • Fixed bug where an extra leading / (path separator) could lead urllib3 to unnecessarily reparse the request URI. (#6644)

Deprecations

  • Requests has officially added support for CPython 3.12 (#6503)
  • Requests has officially added support for PyPy 3.9 and 3.10 (#6641)
  • Requests has officially dropped support for CPython 3.7 (#6642)
  • Requests has officially dropped support for PyPy 3.7 and 3.8 (#6641)

Documentation

  • Various typo fixes and doc improvements.

Packaging

  • Requests has started adopting some modern packaging practices. The source files for the projects (formerly requests) is now located in src/requests in the Requests sdist. (#6506)
  • Starting in Requests 2.33.0, Requests will migrate to a PEP 517 build system using hatchling. This should not impact the average user, but extremely old versions of packaging utilities may have issues with the new packaging format.
Commits
  • d6ebc4a v2.32.0
  • 9a40d12 Avoid reloading root certificates to improve concurrent performance (#6667)
  • 0c030f7 Merge pull request #6702 from nateprewitt/no_char_detection
  • 555b870 Allow character detection dependencies to be optional in post-packaging steps
  • d6dded3 Merge pull request #6700 from franekmagiera/update-redirect-to-invalid-uri-test
  • bf24b7d Use an invalid URI that will not cause httpbin to throw 500
  • 2d5f547 Pin 3.8 and 3.9 runners back to macos-13 (#6688)
  • f1bb07d Merge pull request #6687 from psf/dependabot/github_actions/github/codeql-act...
  • 60047ad Bump github/codeql-action from 3.24.0 to 3.25.0
  • 31ebb81 Merge pull request #6682 from frenzymadness/pytest8
  • Additional commits viewable in compare view


Updates transformers from 4.36.0 to 4.38.0

Release notes

Sourced from transformers's releases.

v4.38: Gemma, Depth Anything, Stable LM; Static Cache, HF Quantizer, AQLM

New model additions

💎 Gemma 💎

Gemma is a new opensource Language Model series from Google AI that comes with a 2B and 7B variant. The release comes with the pre-trained and instruction fine-tuned versions and you can use them via AutoModelForCausalLM, GemmaForCausalLM or pipeline interface!

Read more about it in the Gemma release blogpost: https://hf.co/blog/gemma

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b") model = AutoModelForCausalLM.from_pretrained("google/gemma-2b", device_map="auto", torch_dtype=torch.float16)

input_text = "Write me a poem about Machine Learning." input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")

outputs = model.generate(**input_ids)

You can use the model with Flash Attention, SDPA, Static cache and quantization API for further optimizations !

  • Flash Attention 2
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")

model = AutoModelForCausalLM.from_pretrained( "google/gemma-2b", device_map="auto", torch_dtype=torch.float16, attn_implementation="flash_attention_2" )

input_text = "Write me a poem about Machine Learning." input_ids = tokenizer(input_text, return_tensors="pt").to("cuda")

outputs = model.generate(**input_ids)

  • bitsandbytes-4bit
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2b")

model = AutoModelForCausalLM.from_pretrained( "google/gemma-2b", device_map="auto", load_in_4bit=True ) </tr></table>

... (truncated)

Commits
  • 08ab54a [ gemma] Adds support for Gemma 💎 (#29167)
  • 2de9314 [Maskformer] safely get backbone config (#29166)
  • 476957b 🚨 Llama: update rope scaling to match static cache changes (#29143)
  • 7a4bec6 Release: 4.38.0
  • ee3af60 Add support for fine-tuning CLIP-like models using contrastive-image-text exa...
  • 0996a10 Revert low cpu mem tie weights (#29135)
  • 15cfe38 [Core tokenization] add_dummy_prefix_space option to help with latest is...
  • efdd436 FIX [PEFT / Trainer ] Handle better peft + quantized compiled models (#29...
  • 5e95dca [cuda kernels] only compile them when initializing (#29133)
  • a7755d2 Generate: unset GenerationConfig parameters do not raise warning (#29119)
  • Additional commits viewable in compare view


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dependabot[bot] commented 5 months ago

Superseded by #313.