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fixed small typos in the README.md #8

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Merged
merged 1 commit into from
Nov 8, 2018
Merged

fixed small typos in the README.md #8

merged 1 commit into from
Nov 8, 2018

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gokriznastic
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@VictorSanh VictorSanh merged commit 4850ec5 into huggingface:master Nov 8, 2018
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Many thanks!

qwang70 pushed a commit to DRL36/pytorch-pretrained-BERT that referenced this pull request Mar 2, 2019
@HongyanJiao HongyanJiao mentioned this pull request Sep 19, 2019
LysandreJik added a commit that referenced this pull request Apr 10, 2020
* Initial commit to get BERT + run_glue.py on TPU

* Add README section for TPU and address comments.

* Cleanup TPU bits from run_glue.py (#3)

TPU runner is currently implemented in:
https://github.com/pytorch-tpu/transformers/blob/tpu/examples/run_glue_tpu.py.

We plan to upstream this directly into `huggingface/transformers`
(either `master` or `tpu`) branch once it's been more thoroughly tested.

* Cleanup TPU bits from run_glue.py

TPU runner is currently implemented in:
https://github.com/pytorch-tpu/transformers/blob/tpu/examples/run_glue_tpu.py.

We plan to upstream this directly into `huggingface/transformers`
(either `master` or `tpu`) branch once it's been more thoroughly tested.

* No need to call `xm.mark_step()` explicitly (#4)

Since for gradient accumulation we're accumulating on batches from
`ParallelLoader` instance which on next() marks the step itself.

* Resolve R/W conflicts from multiprocessing (#5)

* Add XLNet in list of models for `run_glue_tpu.py` (#6)

* Add RoBERTa to list of models in TPU GLUE (#7)

* Add RoBERTa and DistilBert to list of models in TPU GLUE (#8)

* Use barriers to reduce duplicate work/resources (#9)

* Shard eval dataset and aggregate eval metrics (#10)

* Shard eval dataset and aggregate eval metrics

Also, instead of calling `eval_loss.item()` every time do summation with
tensors on device.

* Change defaultdict to float

* Reduce the pred, label tensors instead of metrics

As brought up during review some metrics like f1 cannot be aggregated
via averaging. GLUE task metrics depends largely on the dataset, so
instead we sync the prediction and label tensors so that the metrics can
be computed accurately on those instead.

* Only use tb_writer from master (#11)

* Apply huggingface black code formatting

* Style

* Remove `--do_lower_case` as example uses cased

* Add option to specify tensorboard logdir

This is needed for our testing framework which checks regressions
against key metrics writtern by the summary writer.

* Using configuration for `xla_device`

* Prefix TPU specific comments.

* num_cores clarification and namespace eval metrics

* Cache features file under `args.cache_dir`

Instead of under `args.data_dir`. This is needed as our test infra uses
data_dir with a read-only filesystem.

* Rename `run_glue_tpu` to `run_tpu_glue`

Co-authored-by: LysandreJik <[email protected]>
@rabeehk rabeehk mentioned this pull request Nov 23, 2020
wamartin-aml pushed a commit to wamartin-aml/transformers that referenced this pull request Nov 1, 2021
rraminen pushed a commit to rraminen/transformers that referenced this pull request Jun 3, 2022
jameshennessytempus pushed a commit to jameshennessytempus/transformers that referenced this pull request Jun 1, 2023
younesbelkada pushed a commit to younesbelkada/transformers that referenced this pull request Mar 14, 2024
* tokenizer test

* format fix
LysandreJik pushed a commit that referenced this pull request Mar 15, 2024
* Cohere Model Release (#1)

Cohere Model Release

* Remove unnecessary files and code (#2)

Some cleanup

* Delete cohere-model directory (#3)

* Make Fix (#5)

* Pr fixes (#6)

* fixes for pr

* pr fixes for the format

* pr fixes for the format

* src/transformers/models/auto/tokenization_auto.py

* Tokenizer test (#8)

* tokenizer test

* format fix

* Adding Docs and other minor changes (#7)

* Add modeling tests (#9)

* Smol Fix (#11)

* tokenization tests are fixed

* format fixes

* fix pr doc tests

* fix pr doc tests

* fix pr doc tests

* fix pr style check

* small changes in cohere.md

* FIX: Address final comments for transformers integration (#13)

* fix modeling final nits and add proper test file

* for now leave empty tests

* add integration test

* push new test

* fix modeling cohere (#14)

* Update chat templates to use the new API (#15)

---------

Co-authored-by: ahmetustun <[email protected]>
Co-authored-by: Younes Belkada <[email protected]>
Co-authored-by: Matt <[email protected]>
SangbumChoi added a commit to SangbumChoi/transformers that referenced this pull request Aug 22, 2024
jmamou pushed a commit to jmamou/transformers that referenced this pull request Feb 27, 2025
Add unittests for Universal Assisted generation
RyanMullins added a commit to RyanMullins/transformers that referenced this pull request Mar 12, 2025
Gemma3 average pooling changed from 1D to 2D
RyanMullins pushed a commit to RyanMullins/transformers that referenced this pull request Mar 12, 2025
ArthurZucker pushed a commit that referenced this pull request Apr 5, 2025
* 128 experts

* Use default rope

* Unfuse mlp

* Address feedback

* Use None "default" for rope_scaling. Add eot.

* Meta/llama quant compat (#7)

* add quant compatible model & conversion code for llama4

* fix a few issues

* fix a few issues

* minor type mapping fix

---------

Co-authored-by: Lu Fang <[email protected]>

* use a new config parameter to determine which model definition to use for MoE

---------

Co-authored-by: Pedro Cuenca <[email protected]>
Co-authored-by: Lu Fang <[email protected]>
ArthurZucker added a commit that referenced this pull request Apr 5, 2025
* remove one of the last deps

* update fast image processor after refactor

* styling

* more quality of life improvements

* nit

* update

* cleanups

* some cleanups

* vllm updates

* update fake image token

* [convert] Fix typo

* [convert] Strip extraneous bytes from shards

* [convert] Minor fixes

* [convert] Use num_experts

* multi-image fixes in modeling + processor

* fixup size

* 128 experts

* Use default rope

* Unfuse mlp

* simplify a lot inputs embeds merging

* remove .item() 👀

* fix from review

* Address feedback

* Use None "default" for rope_scaling. Add eot.

* set seed

* return aspect ratios and bug fixes

* Moe 128 rebased (#8)

* 128 experts

* Use default rope

* Unfuse mlp

* Address feedback

* Use None "default" for rope_scaling. Add eot.

* Meta/llama quant compat (#7)

* add quant compatible model & conversion code for llama4

* fix a few issues

* fix a few issues

* minor type mapping fix

---------

Co-authored-by: Lu Fang <[email protected]>

* use a new config parameter to determine which model definition to use for MoE

---------

Co-authored-by: Pedro Cuenca <[email protected]>
Co-authored-by: Lu Fang <[email protected]>

* un-comment write_tokenizer from converting script

* remove un-used imports

* [llama4] Pop aspect_ratios from image processor output in Llama4Processor

Signed-off-by: Jon Swenson <[email protected]>

* Fix parameter_count name

* Update src/transformers/models/llama4/configuration_llama4.py

* nit

* Add changes for no_rope, moe_layers, chunked attention. Just need to test all

* Update src/transformers/models/llama4/image_processing_llama4_fast.py

* nit

* fix post merge with main

* support flex attention

* fixes

* fix

* add layer

* small updates

* rebase and delete llm_compressor

* nit

* [llama4/mm] Add back <|image|> token that delimits global tile

* [llama4/mm] Fix Llama 4 image processing unit tests

* add explicit dtype

Signed-off-by: Jon Swenson <[email protected]>

* sdpa works

* comment todo small

* fix model loading

Signed-off-by: Zijing Liu <[email protected]>

* revert

* nits

* small fix for TP on 1 node

* Read new params from config

* Add <|eom|>

* lol don't know how this got here

* adding fp8

* Save processor, fix chat template

* style

* Add boi/eoi tokens

We don't use them.

* fixes for now flex seems to work :)

* updates

* nits

* updates

* missking keys

* add context parallel

* update

* update

* fix

* nits

* add worldsize and make eager attn work for vision

* Ignore new key present in base models

* add tp_plan

* fix nope

Signed-off-by: Zijing Liu <[email protected]>

* minor fix

Signed-off-by: Zijing Liu <[email protected]>

* Clean up Llama4 vision model

* current updates

* add support for `attn_temperature_tuning`

* add floor scale

* add missing attn scales

* push what works, dirty trick for the device synch

* oups

* Fix pad_token_id

See
https://huggingface.co/ll-re/Llama-4-Scout-17B-16E/discussions/2/files
Confirmed in the original codebase.

* fix causallml loading

* rm

* fix tied-weights

* fix sdpa

* push current version

* should work with both short and long

* add compressed_tensos & fix fbgemm tp

* Fix flex impl

* style

* chunking

* try to revert the potentially breaking change

* fix auto factory

* fix shapes in general

* rm processing

* commit cache utils cleanup

* Fix context length

* fix

* allocate

* update tp_plan

* fix SDPA!

* Add support for sparse `Llama4TextMoe` layer from the kernel hub

* cleanup

* better merge

* update

* still broken fixing now

* nits

* revert print

* Write max_position_embeddings and max_model_length

* Update modeling_llama4.py

* Save attention_chunk_size

* Sync eos terminators

* Read initializer_range

* style

* remove `dict`

* fix

* eager should use `chunked_attention_mask`

* revert

* fixup

* fix config

* Revert "Merge pull request #36 from huggingface/sparse-llama4-moe"

This reverts commit ccda19f, reversing
changes made to a515579.

* Fix typo and remove warning with compiled flex and chunked prefill

* Fix MoE vs FF (#41)

* fix

* Use correct no_rope_layers if provided one is empty list

* update tests

* fix

* skipping some tests

* fix fp8 loading

Signed-off-by: Zijing Liu <[email protected]>

* fix text geneartion pipeline

Signed-off-by: Zijing Liu <[email protected]>

* eager needs 4D mask

* fix

* Some cleanup

* fix

* update

* fix

* replace correctly module

* patch

* modulelist

* update

* update

* clean up

* Don't move to `cuda:0` in distributed mode

* restrict to compressed tensors for now

* rm print

* Docs!

* Fixes

* Update docs/source/en/model_doc/llama4.md

Co-authored-by: Pedro Cuenca <[email protected]>

* Fixes

* cuda graph fix

* revert some stuff

* fixup

* styling

* Update src/transformers/models/llama4/modeling_llama4.py

Co-authored-by: Arthur <[email protected]>

* fixup

* commit licence, cleanup here and there and style

* more styling changes

* fix dummies

* fix and clean docstrings

* remove comment

* remove warning

* Only fast image processor is supported

* nit

* trigger CI

* fix issue with flex encoder

* fix dynamic cache

* Code quality

* Code quality

* fix more tests for now

* Code quality

* Code quality

* Nuke bunch of failing stuff

* Code quality

* Code quality

* cleanup removal of slow image processor

* ruff fix fast image processor

* fix

* fix styling

* Docs

* Repo consistency

* Repo consistency

* fix sliding window issue

* separate llama cache

* styling

* Repo consistency

* Repo consistency

* push waht works

* L4 Repo consistency

* Docs

* fix last last alst alst alst alstsaltlsltlaslt

---------

Signed-off-by: Jon Swenson <[email protected]>
Signed-off-by: Zijing Liu <[email protected]>
Co-authored-by: yonigozlan <[email protected]>
Co-authored-by: Pedro Cuenca <[email protected]>
Co-authored-by: Pablo Montalvo <[email protected]>
Co-authored-by: Pablo Montalvo <[email protected]>
Co-authored-by: Keyun Tong <[email protected]>
Co-authored-by: Zijing Liu <[email protected]>
Co-authored-by: Lu Fang <[email protected]>
Co-authored-by: Zijing Liu <[email protected]>
Co-authored-by: Jon Swenson <[email protected]>
Co-authored-by: jmswen <[email protected]>
Co-authored-by: MekkCyber <[email protected]>
Co-authored-by: Mohamed Mekkouri <[email protected]>
Co-authored-by: Mohit Sharma <[email protected]>
Co-authored-by: Yong Hoon Shin <[email protected]>
Co-authored-by: Marc Sun <[email protected]>
Co-authored-by: drisspg <[email protected]>
Co-authored-by: Cyril Vallez <[email protected]>
Co-authored-by: Daniël de Kok <[email protected]>
Co-authored-by: Lysandre <[email protected]>
Co-authored-by: Ye (Charlotte) Qi <[email protected]>
Co-authored-by: ydshieh <[email protected]>
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2 participants