- 01 May, 2024 2 commits
-
-
Raushan Turganbay authored
* move scaling to nn.Module * let the test be here for now (need to fix) * failing tests * last failing models * Revert commit 4c14817f38 * clean-up * oops forgot * codestyle * raise NotImplemented when possible * Update tests/test_modeling_common.py Co-authored-by:
amyeroberts <22614925+amyeroberts@users.noreply.github.com> * skip tests in respective modeling files --------- Co-authored-by:
-
Raushan Turganbay authored
use text config's vocab size
-
- 30 Apr, 2024 3 commits
-
-
Yih-Dar authored
* fix * add test --------- Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
-
Jiarui Xu authored
* add_blip_get_multimodal_feautres * Fix docstring error * reimplement get_multimodal_features * fix error * recheck code quality * add new necessary tests
-
Joao Gante authored
-
- 26 Apr, 2024 3 commits
-
-
Eduardo Pacheco authored
* Fixed SegGptImageProcessor to handle 2D and 3D prompt mask inputs * Added new test to check prompt mask equivalence * New proposal * Better proposal * Removed unnecessary method * Updated seggpt docs * Introduced do_convert_rgb * nits
-
amyeroberts authored
* Enable instantiating model with pretrained backbone weights * Clarify pretrained import * Use load_backbone instead * Add backbone_kwargs to config * Fix up * Add tests * Tidy up * Enable instantiating model with pretrained backbone weights * Update tests so backbone checkpoint isn't passed in * Clarify pretrained import * Update configs - docs and validation check * Update src/transformers/utils/backbone_utils.py Co-authored-by:
Arthur <48595927+ArthurZucker@users.noreply.github.com> * Clarify exception message * Update config init in tests * Add test for when use_timm_backbone=True * Use load_backbone instead * Add use_timm_backbone to the model configs * Add backbone_kwargs to config * Pass kwargs to constructors * Draft * Fix tests * Add back timm - weight naming * More tidying up * Whoops * Tidy up * Handle when kwargs are none * Update tests * Revert test changes * Deformable detr test - don't use default * Don't mutate; correct model attributes * Add some clarifying comments * nit - grammar is hard --------- Co-authored-by:
-
JB (Don) authored
* Adding SDPA support for BERT * Using the proper input name for testing model input in inference() * Adding documentation for SDPA in BERT model page * Use the stable link for the documentation * Adding a gate to only call .contiguous() for torch < 2.2.0 * Additions and fixes to the documentation * Minor updates to documentation * Adding extra requirements needed for the contiguous() bug * Adding "Adapted from" in plcae of the "Copied from" * Add benchmark speedup tables to the documentation * Minor fixes to the documentation * Use ClapText as a replacemenet for Bert in the Copied-From * Some more fixes for the fix-copies references * Overriding the test_eager_matches_sdpa_generate in bert tests to not load with low_cpu_mem_usage [test all] * Undo changes to separate test * Refactored SDPA self attention code for KV projections * Change use_sdpa to attn_implementation * Fix test_sdpa_can_dispatch_on_flash by preparing input (required for MultipleChoice models)
-
- 25 Apr, 2024 3 commits
-
-
Raushan Turganbay authored
-
Yoach Lacombe authored
* first modeling code * make repository * still WIP * update model * add tests * add latest change * clean docstrings and copied from * update docstrings md and readme * correct chroma function * correct copied from and remove unreleated test * add doc to toctree * correct imports * add convert script to notdoctested * Add suggestion from Sanchit Co-authored-by:
Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com> * correct get_uncoditional_inputs docstrings * modify README according to SANCHIT feedback * add chroma to audio utils * clean librosa and torchaudio hard dependencies * fix FE * refactor audio decoder -> audio encoder for consistency with previous musicgen * refactor conditional -> encoder * modify sampling rate logics * modify license at the beginning * refactor all_self_attns->all_attentions * remove ignore copy from causallm generate * add copied from for from_sub_models * fix make copies * add warning if audio is truncated * add copied from where relevant * remove artefact * fix convert script * fix torchaudio and FE * modify chroma method according to feedback-> better naming * refactor input_values->input_features * refactor input_values->input_features and fix import fe * add input_features to docstrigs * correct inputs_embeds logics * remove dtype conversion * refactor _prepare_conditional_hidden_states_kwargs_for_generation ->_prepare_encoder_hidden_states_kwargs_for_generation * change warning for chroma length * Update src/transformers/models/musicgen_melody/convert_musicgen_melody_transformers.py Co-authored-by:
-
amyeroberts authored
-
- 24 Apr, 2024 4 commits
-
-
Gustavo de Rosa authored
* chore(root): Initial commit of Phi-3 files. * fix(root): Fixes Phi-3 missing on readme. * fix(root): Ensures files are consistent. * fix(phi3): Fixes unit tests. * fix(tests): Fixes style of phi-3 test file. * chore(tests): Adds integration tests for Phi-3. * fix(phi3): Removes additional flash-attention usage, .e.g, swiglu and rmsnorm. * fix(phi3): Fixes incorrect docstrings. * fix(phi3): Fixes docstring typos. * fix(phi3): Adds support for Su and Yarn embeddings. * fix(phi3): Improves according first batch of reviews. * fix(phi3): Uses up_states instead of y in Phi3MLP. * fix(phi3): Uses gemma rotary embedding to support torch.compile. * fix(phi3): Improves how rotary embedding classes are defined. * fix(phi3): Fixes inv_freq not being re-computed for extended RoPE. * fix(phi3): Adds last suggestions to modeling file. * fix(phi3): Splits inv_freq calculation in two lines.
-
Eduardo Pacheco authored
* Fixed main train issues * Added loss test * Update src/transformers/models/seggpt/modeling_seggpt.py Co-authored-by:
-
Arthur authored
* nit * nit and fmt skip * fixup * Update src/transformers/convert_slow_tokenizer.py Co-authored-by:
-
Pavel Iakubovskii authored
* Add test for square image that fails * Fix for square images * Extend test cases * Fix resizing in tests * Style fixup
-
- 23 Apr, 2024 3 commits
-
-
Arthur authored
* push legacy to fast as well * super strange * Update src/transformers/convert_slow_tokenizer.py * make sure we are BC * fix Llama test * nit * revert * more test * style * update * small update w.r.t tokenizers * nit * don't split * lol * add a test for `add_prefix_space=False` * fix gemma tokenizer as well * update * fix gemma * nicer failures * fixup * update * fix the example for legacy = False * use `huggyllama/llama-7b` for the PR doctest * nit * use from_slow * fix llama
-
Fanli Lin authored
* add cuda flag * check for sdpa * add bitsandbytes
-
Eduardo Pacheco authored
* Added cross attention support * Fixed dtypes * Fixed assumption * Moved to decoder
-
- 22 Apr, 2024 3 commits
-
-
Kamil Akesbi authored
* add sdpa to wav2vec. Co-authored-by:
kamilakesbi <kamil@huggingface.co> Co-authored-by:
jp1924 <jp42maru@gmail.com> * add fa2 to wav2vec2 * add tests * fix attention_mask compatibility with fa2 * minor dtype fix * replace fa2 slow test * fix fa2 slow test * apply code review + add fa2 batch test * add sdpa and fa2 to hubert * sdpa and fa2 to data2vec_audio * sdpa and fa2 to Sew * sdpa to unispeech + unispeech sat * small fix * attention mask in tests Co-authored-by:
kamil@huggingface.co <kamil.akesbi@gmail.com> Co-authored-by:
-
Pavel Iakubovskii authored
* Add class_embed to tied weights for DETA * Fix test_tied_weights_keys for DETA model * Replace error raise with assert statement
-
Joao Gante authored
fix test
-
- 19 Apr, 2024 5 commits
-
-
Jo茫o David authored
* Duplicate swiftformer * Convert SwiftFormerPatchEmbedding * Convert SwiftFormerEmbeddings * Convert TFSwiftFormerMlp * Convert TFSwiftFormerConvEncoder * Convert TFSwiftFormerLocalRepresentation * convert TFSwiftFormerEncoderBlock * Convert SwiftFormerStage * Convert SwiftFormerEncoder * Add TFSWiftFormerPreTrainedModel * Convert SwiftFormerForImageClassification * Add kwargs and start drop path * Fix syntax * Change Model class name * Add TFSwiftFormer to __init__ * Duplicate test_modeling_swiftformer * First test conversions * Change require_torch to require_tf * Add exports to swiftformer __init__ * Add TFSwiftFormerModel wrapper * Fix __init__ and run black * Remove docstring from MainLayer, fix padding * Use keras.layers.Activation on keras.Sequential * Fix swiftformer exports * Fix activation layer from config * Remove post_inits * Use tf.keras.layers.ZeroPadding2D * Convert torch normalize * Change tf test input shape * Fix softmax and reduce_sum * Convert expand_dims and repeat * Add missing reshape and tranpose * Simplify TFSwiftFormerEncoderBlock.call * Fix mismatch in patch embeddings * Fix expected output shape to match channels last * Fix swiftformer typo * Disable test_onnx * Fix TFSwiftFormerForImageClassification call * Add unpack inputs * Convert flatten(2).mean(-1) * Change vision dummy inputs (to be reviewed) * Change test_forward_signature to use .call * Fix @unpack_inputs * Set return_tensors="tf" and rename class * Rename wrongly named patch_embeddings layer * Add serving_output and change dummy_input shape * Make dimensions BCHW and transpose inside embedding layer * Change SwiftFormerEncoderBlock * Fix ruff problems * Add image size to swiftformer config * Change tranpose to MainLayer and use -1 for reshape * Remove serving_outputs and dummy_inputs * Remove test_initialization test from tf model * Make Sequential component a separate layer * Fix layers' names * Tranpose encoder outputs * Fix tests and check if hidden states is not None * Fix TFSwiftFormerForImageClassification * Run make fixup * Run make fix-copies * Update modeling_tf_auto * Update docs * Fix modeling auto mapping * Update modelint_tf_swiftformer docs * Fill image_size doc and type * Add reduction=None to loss computation * Update docs * make style * Debug: Delete the tip to see if that changes anything * Re-add tip * Remove add_code_sample_docstrings * Remove unused import * Get the debug to actually tell us the problem it has with the docs * Try a substitution to match the PyTorch file? * Add swiftformer to ignore list * Add build() methods * Update copyright year Co-authored-by:
Matt <Rocketknight1@users.noreply.github.com> * Raise error if drop_path_rate > 0.0 * Apply suggestions from code review Replace (self.dim), with self.dim, Co-authored-by:
Matt <rocketknight1@gmail.com> Co-authored-by:
-
Raushan Turganbay authored
* remove seq length from generation tests * style and quality * [test_all] & PR suggestion Co-authored-by:
Joao Gante <joaofranciscocardosogante@gmail.com> * Update tests/generation/test_utils.py Co-authored-by:
-
Sanchit Gandhi authored
* fix tests * style * more fixes * move model to device * move logits to cpu * update expected values * use ungated dataset * fix * fix * update --------- Co-authored-by: -
Sanchit Gandhi authored
fixes
-
NielsRogge authored
* Add special tokens * Add special tokens * Use fmt * Uncomment code * Add test * Remove scripts * Address comments * Improve tests * Address comment * Remove flag
-
- 18 Apr, 2024 4 commits
-
-
Abhi Venigalla authored
* wip * fix __init__.py * add docs * Apply suggestions from code review Co-authored-by:
Wing Lian <wing.lian@gmail.com> * default to using router_aux_loss_coef over ffn_config[moe_loss_weight] * fix _flash_attn_uses_top_left_mask and is_causal * fix tests path * don't use token type IDs * follow Llama and remove token_type_ids from test * init ConfigTester differently so tests pass * remove multiple choice test * remove question + answer test * remove sequence classification test * remove token classification test * copy Llama tests and remove token_type_ids from test inputs * do not test pruning or headmasking; style code * add _tied_weights_keys parameter to pass test * add type hints * fix type check * update config tester * remove masked_lm test * remove encoder tests * initialize DbrxModelTester with correct params * style * torch_dtype does not rely on torch * run make fixup, fix-copies * use https://huggingface.co/v2ray/dbrx-base-fixed/blob/main/modeling_dbrx.py * add copyright info * fix imports and DbrxRotaryEmbedding * update DbrxModel docstring * use copies * change model path in docstring * use config in DbrxFFN * fix flashattention2, sdpaattention * input config to DbrXAttention, DbrxNormAttentionNorm * more fixes * fix * fix again! * add informative comment * fix ruff? * remove print statement + style * change doc-test * fix doc-test * fix docstring * delete commented out text * make defaults match dbrx-instruct * replace `router_aux_loss_coef` with `moe_loss_weight` * is_decoder=True * remove is_decoder from configtester * implement sdpa properly * make is_decoder pass tests * start on the GenerationTesterMixin tests * add dbrx to sdpa documentation * skip weight typing test * style * initialize smaller model Co-authored-by:
Abhi Venigalla <abhi.venigalla@databricks.com> Co-authored-by:
Eitan Turok <eitan.turok@databricks.com> Co-authored-by:
Eitan Turok <150733043+eitanturok@users.noreply.github.com> Co-authored-by:
Eitan Turok <eitanturok@gmail.com> Co-authored-by:
Your Name <you@example.com> Co-authored-by:
Mihir Patel <mihir.v.patel7@gmail.com> Co-authored-by:
-
tomeras91 authored
* Add jamba arch * apply "make fix-copies" changes * fix link to model in JambaConfig docstring * Add n_ctx in modeling file because repo-consistency wants that * Add jamba to flash attention and sdpa documentation * mamba dt_proj quant fix now works for LoRA as well * override test_left_padding_compatibility and use a more permissive tolerance. left padding numerical difference are accentuated by mamba layers * add jamba to tokenization auto * fix comments of shape (PR #24 in the model page: https://huggingface.co/ai21labs/Jamba-v0.1/discussions/24) * simple PR fixes * remove unnecessary kwargs from JambaAttentionDecoderLayer and JambaMambaDecoderLayer * remove the LoRA hack for the mamba dt_proj bias. It was solved in huggingface/peft#1530 (https://github.com/huggingface/peft/pull/1530) * Add copied comment on JambaMLP (it's the same as MixtralMLP) * remove padding_mask warnings. It's not supported anymore * fix docstring. Float instead of int * A few more minor PR fixes * (1) lowercase names for mamba layernorms (2) remove _apply_inner_layernorms and do it directly in the forward pass * Return None attention weights from mamba layers. Append to all attentions only if not None. * remove some leftover jamba archive lists * Better separation between expert vs non-expert layers. non-expert layers return None as router_logits, and it is not concatenated to all_router_logits returned from JambaModel * no need to take router_logits at config.expert_layer_offset anymore. result.router_logits now holds results only for expert layers * Add Jamba paper on READMEs * (1) rename n_ctx -> max_position_embeddings (2) don't use it in the modeling file since it's not needed (set it as an exception to check_config_attributes) * Add copied from comment * remove the code path for apply_inner_layernorms=False. Jamba always has the inner mamba layernorms * clearer docstring for _convert_to_standard_cache * style fixes * Change calc_logits_for_entire_prompt (bool) to num_logits_to_keep (int). Adapt assisted decoding code tp use it. Also small change in low memory beam search decoding path to support this new int value in model_inputs * rename test so it still overrides what its meant to override * draft * oups * nit * remove more complexe logic * fix names used in config * fix fix fix * style * fix some more failing tests * generate did not init the cache
馃檭 * more small nits * typo * config.mamba_expand * config.hidden_size for the intermediate size of the mamba shapes * fix init of pkv with torch.tensor() * empty tensor * fix some init issues * stupid changes required by generate because it does not even support it's own DynamicCache class * more fixes * fix general assisted gen cache_position bug * tests passing * Add offsets and periods as SPECIAL_CASES_TO_ALLOW in check_config_attributes.py * fix reorder_cache to reorder mamba states and override some more functions in HybridMambaAttentionDynamicCache * no need to override test_past_key_values_format() and _check_past_key_values_for_generate() in tests anymore * fix docstrings and typehints for past_key_values * style fixes * fix docs * change typehint due to copy from Mixtral * forgot import * import order * Add configuration_jamba and modeling_jamba to not_doctested because the model is too big to download (in docstring of JambaForCausalLM.forward) * Add integration test with tiny tandom Jamba model on hub * fix flash attention cache shapes * bring back forgotten hidden states * rename HybridMambaAttentionDynamicCache.seqlen_offset to has_previous_state (and make bool) and bugfix - it should be set to True after a finished forward pass of the entire model * align integration test after modeling fixes * bugfix - mamba can use precomputed states only of forward pass is on a single token * bugfix - mamba can use precomputed states only if they match the batch size * typo * remove making _prepare_4d_causal_attention_mask a leaf function * stop using past_seq_len.get_seq_length(). Use cache positions instead. Adjust test (test_decoder_model_past_with_large_inputs) accordingly --------- Co-authored-by:Arthur Zucker <arthur.zucker@gmail.com> Co-authored-by:
Joao Gante <joao@huggingface.co>
-
Pavel Iakubovskii authored
* Fix multiline processing * Update test for token2json
-
Alexander Visheratin authored
* Added flash attention 2. * Fixes. * Fix inheritance. * Fixed init. * Remove stuff. * Added documentation. * Add FA2 to M2M100 documentation. * Add test. * Fixed documentation. * Update src/transformers/models/m2m_100/modeling_m2m_100.py Co-authored-by:
Younes Belkada <49240599+younesbelkada@users.noreply.github.com> * Update docs/source/en/model_doc/nllb.md Co-authored-by:
-
- 17 Apr, 2024 3 commits
-
-
Shane A authored
* Add OLMo using add-new-model-like with Llama * Fix incorrect tokenizer for OLMo * Copy-paste relevant OLMo methods and their imports * Add OLMo config * Modify OLMo config to follow HF conventions * Remove unneeded Llama code from OLMo model * Add ability for OLMo model to output attentions * Add OLMoPreTrainedModel and OLMoModel * Add OLMoForCausalLM * Minor fixes to OLMo model for style and missing functions * Implement OLMo tokenizer * Implement OLMo to HF conversion script * Add tests for OLMo model * Add tests for OLMo fast tokenizer * Add auto-generated dummy objects * Remove unimplemented OLMo classes from auto and init classes and re-format * Add README and associated auto-generated files * Use OLMo names for common properties * Run make fixup * Remove `|` from OLMo typing * Remove unneeded tokenization_olmo.py * Revert model, config and converter to add-new-model-like Llama * Move logic for adding bos/eos token into GPTNeoxTokenizerFast * Change OLMoConfig defaults to match OLMo-7B * Use GPTNeoXToknizerFast in OLMo tokenizer tests * Modify auto-generated OLMoModelTests to work for OLMo * Add non-parametric layer norm OLMoLayerNorm * Update weight conversion script for OLMo * Fix __init__ and auto structure for OLMo * Fix errors from make fixup * Remove OLMoTokenizerFast from documentation * Add missing 'Copied from' for OLMoModel._update_causal_mask * Run make fix-copies * Rearrange string replacements in OLMoForCausalLM Copied from * Move OLMo and Llama CausalLM.forward example into global constants * Fix OLMO_GENERATION_EXAMPLE doc string typo * Add option for qkv clipping to OLMo * Rearrange OLMoConfig kwargs in convert_olmo_weights_to_hf * Add clip_qkv to OLMoConfig in convert_olmo_weights_to_hf * Fix OLMo tokenization bug using conversion script * Keep model in full precision after conversion * Do not add eos token automatically * Update references to OLMo model in HF Hub * Do not add eos token during encoding by default * Fix Llama generation example * Run make fixup * OLMo 7B integration test fix * Remove unneeded special case for OLMoConfig * OLMo 7B Twin 2T integration test fix * Fix test_model_7b_greedy_generation * Remove test_compile_static_cache * Fix OLMo and Llama generation example * Run make fixup * Revert "OLMo 7B integration test fix" This reverts commit 4df56a4b150681bfa559846f40e9b7b7f97d7908. * Revert "OLMo 7B Twin 2T integration test fix" This reverts commit 9ff65a4a294ace89ab047b793ca55e623a9ceefc. * Ungate 7B integration tests and fix greedy generation test * Add retries for flaky test_eager_matches_sdpa_generate * Fix output of doc example for OLMoForCausalLM.forward * Downsize OLMo doc test for OLMoForCausalLM.forward to 1B model * Try fix incorrect characters in OLMoForCausalLM.forward doct test * Try fix incorrect characters in OLMoForCausalLM.forward doc test using end quotes * Remove pretraining_tp from OLMo config and model * Add missing 'Copied from' instances * Remove unneeded causal_mask from OLMoModel * Revert Llama changes * Ignore copy for OLMoForCausalLM.forward * Change 'OLMo' to 'Olmo' in classes * Move minimal OLMo tokenization tests to model tests * Add missed 'Copied from' for repeat_kv
-
st81 authored
* Add create token type ids to CodeGenTokenizer * Fix inconsistent length of token type ids * Format source codes * Fix inconsistent order of methods * Update docstring * add test_tokenizer_integration test * Format source codes * Add `copied from` comment to CodeGenTokenizerFast * Add doc of create_token_type_ids_from_sequences * Make return_token_type_ids False by default * Make test_tokenizer_integration as slow test * Add return_token_type_ids to tokenizer init arg * Add test for tokenizer's init return_token_type_ids * Format source codes
-
Raushan Turganbay authored
* tracing for mistral * typo * fix copies
-
- 16 Apr, 2024 1 commit
-
-
amyeroberts authored
* BLIP - fix pt-tf equivalence test * Update tests/models/blip/test_modeling_blip.py * Update more model tests
-
- 15 Apr, 2024 3 commits
-
-
amyeroberts authored
* Initial add model additions * Test * All weights loading * Can perform full forward pass * Local and remote the same * Matching local and remote * Fixup * Idefics2Model importable; fixup docstrings * Don't skip by default * Remove deprecated use_resampler arg * Remove self.config * DecoupledLinear takes config * Tidy up * Enable eager attention and tidy up * Most tests passing * Update for batch of processed images * Add image processor * Update doc pages * Update conversion script * Remove erroneous breakpoint * Remove accidendtal spelling change * Update to reflect changes on hub - make generate work * Fix up * Image processor tests * Update tests * Add a processor * Add a processor * Update convert script * Update modeling file - remove fixmes * Bug fix * Add processing test * Use processor * Fix up * Update src/transformers/models/idefics2/modeling_idefics2.py Co-authored-by:
Victor SANH <victorsanh@gmail.com> * Update src/transformers/models/idefics2/modeling_idefics2.py Co-authored-by:
Pablo Montalvo <39954772+molbap@users.noreply.github.com> Co-authored-by:
-
Fanli Lin authored
add gpu flag
-
Sai-Suraj-27 authored
Replace deprecated assertEquals with assertEqual.
-
- 12 Apr, 2024 1 commit
-
-
Yih-Dar authored
fix Co-authored-by:
-
- 11 Apr, 2024 2 commits
-
-
NielsRogge authored
* Remove auto class * Update ImagePointDescriptionOutput * Update model outputs * Rename output class * Revert "Remove auto class" This reverts commit ed4a8f549d79cdb0cdf7aa74205a185c41471519. * Address comments
-
lewtun authored
-
