* Fix wrong position_ids shape in doc
Supported by ClvpDecoder.forward, line 1212--1215:
src/transformers/models/clvp/modeling_clvp.py:
1212 if inputs_embeds is None:
1213 inputs_embeds = self.input_embeds_layer(input_ids)
1214 position_embeds = self.position_embeds_layer(position_ids)
1215 inputs_embeds = inputs_embeds + position_embeds
* Fix possibly wrong input_ids shape in doc
Since 'input_ids_length' was mentioned immediately after the shape `(batch_size, sequence_length)`, it doesn't make sense to me for `input_ids` to have such shape---IMO it ought to have shape `(batch_size, input_ids_length)` instead.
* Fix possibly wrong inputs_embeds shape in doc
Supported by CTRLModel.forward, line 448--449:
src/transformers/models/ctrl/modeling_ctrl.py:
448 if inputs_embeds is None:
449 inputs_embeds = self.w(input_ids)
This commit is introduced due to commit 6f36b56497828642b65f54ea26aa4064186de57a.
* Fix possibly wrong token_type_ids shape in doc
Supported by CTRLModel.forward, line 441--460:
src/transformers/models/ctrl/modeling_ctrl.py:
441 if token_type_ids is not None:
442 token_type_ids = token_type_ids.view(-1, input_shape[-1])
443 token_type_embeds = self.w(token_type_ids)
444 token_type_embeds *= np.sqrt(self.d_model_size)
445 else:
446 token_type_embeds = 0
447
448 if inputs_embeds is None:
449 inputs_embeds = self.w(input_ids)
450 # inputs_embeds = embedded.unsqueeze(0) if len(input_ids.shape)<2 else embedded
451 seq_len = input_shape[-1]
452 mask = torch.triu(torch.ones(seq_len + past_length, seq_len + past_length), 1).to(device)
453
454 inputs_embeds *= np.sqrt(self.d_model_size)
455
456 # `self.pos_encoding` won't be sent to the correct device along the model, so we do it manually.
457 self.pos_encoding = self.pos_encoding.to(device)
458 pos_embeds = self.pos_encoding[position_ids, :]
459
460 hidden_states = inputs_embeds + pos_embeds + token_type_embeds
This commit is introduced due to commit 6f36b56497828642b65f54ea26aa4064186de57a.
* Fix possibly wrong position_ids shape in doc
Supported by CTRLModel.forward, line 448--460:
src/transformers/models/ctrl/modeling_ctrl.py:
448 if inputs_embeds is None:
449 inputs_embeds = self.w(input_ids)
450 # inputs_embeds = embedded.unsqueeze(0) if len(input_ids.shape)<2 else embedded
451 seq_len = input_shape[-1]
452 mask = torch.triu(torch.ones(seq_len + past_length, seq_len + past_length), 1).to(device)
453
454 inputs_embeds *= np.sqrt(self.d_model_size)
455
456 # `self.pos_encoding` won't be sent to the correct device along the model, so we do it manually.
457 self.pos_encoding = self.pos_encoding.to(device)
458 pos_embeds = self.pos_encoding[position_ids, :]
459
460 hidden_states = inputs_embeds + pos_embeds + token_type_embeds
This commit is introduced due to commit 6f36b56497828642b65f54ea26aa4064186de57a.
* Fix wrong token_type_ids shape in doc
Supported by TFCTRLMainLayer.call, line 376--394:
src/transformers/models/ctrl/modeling_tf_ctrl.py:
376 if token_type_ids is not None:
377 token_type_ids = tf.reshape(token_type_ids, [-1, shape_list(token_type_ids)[-1]])
378 token_type_embeds = self.w(token_type_ids)
379 token_type_embeds *= tf.math.sqrt(tf.cast(self.d_model_size, dtype=token_type_embeds.dtype))
380 else:
381 token_type_embeds = tf.constant(0.0)
382 position_ids = tf.reshape(position_ids, [-1, shape_list(position_ids)[-1]])
383
384 if inputs_embeds is None:
385 check_embeddings_within_bounds(input_ids, self.w.input_dim)
386 inputs_embeds = self.w(input_ids)
387 seq_len = input_shape[-1]
388 mask = 1 - tf.linalg.band_part(tf.ones((seq_len, seq_len)), -1, 0)
389
390 inputs_embeds *= tf.math.sqrt(tf.cast(self.d_model_size, inputs_embeds.dtype))
391
392 pos_embeds = tf.gather(self.pos_encoding, position_ids)
393 pos_embeds = tf.cast(pos_embeds, dtype=token_type_embeds.dtype)
394 hidden_states = inputs_embeds + pos_embeds + token_type_embeds
* Fix wrong position_ids shape in doc
Supported by TFCTRLMainLayer.call, line 384--394:
src/transformers/models/ctrl/modeling_tf_ctrl.py:
384 if inputs_embeds is None:
385 check_embeddings_within_bounds(input_ids, self.w.input_dim)
386 inputs_embeds = self.w(input_ids)
387 seq_len = input_shape[-1]
388 mask = 1 - tf.linalg.band_part(tf.ones((seq_len, seq_len)), -1, 0)
389
390 inputs_embeds *= tf.math.sqrt(tf.cast(self.d_model_size, inputs_embeds.dtype))
391
392 pos_embeds = tf.gather(self.pos_encoding, position_ids)
393 pos_embeds = tf.cast(pos_embeds, dtype=token_type_embeds.dtype)
394 hidden_states = inputs_embeds + pos_embeds + token_type_embeds
* Fix wrong inputs_embeds shape in doc
Supported by TFCTRLMainLayer.call, line 384--394:
src/transformers/models/ctrl/modeling_tf_ctrl.py:
384 if inputs_embeds is None:
385 check_embeddings_within_bounds(input_ids, self.w.input_dim)
386 inputs_embeds = self.w(input_ids)
387 seq_len = input_shape[-1]
388 mask = 1 - tf.linalg.band_part(tf.ones((seq_len, seq_len)), -1, 0)
389
390 inputs_embeds *= tf.math.sqrt(tf.cast(self.d_model_size, inputs_embeds.dtype))
391
392 pos_embeds = tf.gather(self.pos_encoding, position_ids)
393 pos_embeds = tf.cast(pos_embeds, dtype=token_type_embeds.dtype)
394 hidden_states = inputs_embeds + pos_embeds + token_type_embeds
* Fix wrong inputs_embeds shape in doc
Supported by ClvpDecoder.forward, line 1212--1213:
src/transformers/models/clvp/modeling_clvp.py:
1212 if inputs_embeds is None:
1213 inputs_embeds = self.input_embeds_layer(input_ids)
* Fix wrong position_ids shape in doc
Supported by FlaxGemmaPreTrainedModel.__call__, line 502--508:
src/transformers/models/gemma/modeling_flax_gemma.py:
502 batch_size, sequence_length = input_ids.shape
503
504 if position_ids is None:
505 if past_key_values is not None:
506 raise ValueError("Make sure to provide `position_ids` when passing `past_key_values`.")
507
508 position_ids = jnp.broadcast_to(jnp.arange(sequence_length)[None, :], (batch_size, sequence_length))
* Fix wrong position_ids shape in doc
Supported by FlaxGPT2PreTrainedModel.__call__, line 482--488:
src/transformers/models/gpt2/modeling_flax_gpt2.py:
482 batch_size, sequence_length = input_ids.shape
483
484 if position_ids is None:
485 if past_key_values is not None:
486 raise ValueError("Make sure to provide `position_ids` when passing `past_key_values`.")
487
488 position_ids = jnp.broadcast_to(jnp.arange(sequence_length)[None, :], (batch_size, sequence_length))
* Fix wrong position_ids shape in doc
Supported by GPT2Model.forward, line 918--921:
src/transformers/models/gpt2/modeling_gpt2.py:
918 if inputs_embeds is None:
919 inputs_embeds = self.wte(input_ids)
920 position_embeds = self.wpe(position_ids)
921 hidden_states = inputs_embeds + position_embeds.to(inputs_embeds.device)
* Fix wrong inputs_embeds shape in doc
Supported by GPT2Model.forward, line 918--919:
src/transformers/models/gpt2/modeling_gpt2.py:
918 if inputs_embeds is None:
919 inputs_embeds = self.wte(input_ids)
* Fix wrong labels shape in doc
Supported by GPT2LMHeadModel.forward, line 1156--1157:
src/transformers/models/gpt2/modeling_gpt2.py:
1156 Labels for language modeling. Note that the labels **are shifted** inside the model, i.e. you can set
1157 `labels = input_ids` Indices are selected in `[-100, 0, ..., config.vocab_size]` All labels set to `-100`
* Fix wrong labels shape in doc
Supported by GPT2DoubleHeadsModel.forward, line 1314--1315:
src/transformers/models/gpt2/modeling_gpt2.py:
1314 Labels for language modeling. Note that the labels **are shifted** inside the model, i.e. you can set
1315 `labels = input_ids`. Indices are selected in `[-100, 0, ..., config.vocab_size - 1]`. All labels set to
* Fix wrong token_type_ids shape in doc
Supported by TFGPT2MainLayer.call, line 486--500:
src/transformers/models/gpt2/modeling_tf_gpt2.py:
486 if inputs_embeds is None:
487 check_embeddings_within_bounds(input_ids, self.config.vocab_size)
488 inputs_embeds = self.wte(input_ids)
489
490 position_embeds = self.wpe(position_ids)
491
492 if token_type_ids is not None:
493 token_type_ids = tf.reshape(token_type_ids, [-1, shape_list(token_type_ids)[-1]])
494 token_type_embeds = self.wte(token_type_ids)
495 else:
496 token_type_embeds = tf.constant(0.0)
497
498 position_embeds = tf.cast(position_embeds, dtype=inputs_embeds.dtype)
499 token_type_embeds = tf.cast(token_type_embeds, dtype=inputs_embeds.dtype)
500 hidden_states = inputs_embeds + position_embeds + token_type_embeds
* Fix wrong position_ids shape in doc
Supported by TFGPT2MainLayer.call, line 486--500:
src/transformers/models/gpt2/modeling_tf_gpt2.py:
486 if inputs_embeds is None:
487 check_embeddings_within_bounds(input_ids, self.config.vocab_size)
488 inputs_embeds = self.wte(input_ids)
489
490 position_embeds = self.wpe(position_ids)
491
492 if token_type_ids is not None:
493 token_type_ids = tf.reshape(token_type_ids, [-1, shape_list(token_type_ids)[-1]])
494 token_type_embeds = self.wte(token_type_ids)
495 else:
496 token_type_embeds = tf.constant(0.0)
497
498 position_embeds = tf.cast(position_embeds, dtype=inputs_embeds.dtype)
499 token_type_embeds = tf.cast(token_type_embeds, dtype=inputs_embeds.dtype)
500 hidden_states = inputs_embeds + position_embeds + token_type_embeds
* Fix wrong inputs_embeds shape in doc
Supported by TFGPT2MainLayer.call, line 486--488:
src/transformers/models/gpt2/modeling_tf_gpt2.py:
486 if inputs_embeds is None:
487 check_embeddings_within_bounds(input_ids, self.config.vocab_size)
488 inputs_embeds = self.wte(input_ids)
* Fix wrong position_ids shape in doc
Supported by GPTBigCodeModel.forward, line 962--965:
src/transformers/models/gpt_bigcode/modeling_gpt_bigcode.py:
962 if inputs_embeds is None:
963 inputs_embeds = self.wte(input_ids)
964 position_embeds = self.wpe(position_ids)
965 hidden_states = inputs_embeds + position_embeds.to(inputs_embeds.device)
* Fix wrong inputs_embeds shape in doc
Supported by GPTBigCodeModel.forward, line 962--963:
src/transformers/models/gpt_bigcode/modeling_gpt_bigcode.py:
962 if inputs_embeds is None:
963 inputs_embeds = self.wte(input_ids)
* Fix wrong labels shape in doc
Supported by GPTBigCodeForCausalLM.forward, line 1158--1159:
src/transformers/models/gpt_bigcode/modeling_gpt_bigcode.py:
1158 Labels for language modeling. Note that the labels **are shifted** inside the model, i.e. you can set
1159 `labels = input_ids` Indices are selected in `[-100, 0, ..., config.vocab_size]` All labels set to `-100`
* Fix wrong position_ids shape in doc
Supported by FlaxGPTNeoModule.__call__, line 549--552:
src/transformers/models/gpt_neo/modeling_flax_gpt_neo.py:
549 input_embeds = self.wte(input_ids.astype("i4"))
550 position_embeds = self.wpe(position_ids.astype("i4"))
551
552 hidden_states = input_embeds + position_embeds
* Fix wrong position_ids shape in doc
Supported by GPTNeoModel.forward, line 685--720:
src/transformers/models/gpt_neo/modeling_gpt_neo.py:
685 if inputs_embeds is None:
686 inputs_embeds = self.wte(input_ids)
687
688 # kept for BC (non `Cache` `past_key_values` inputs)
689 return_legacy_cache = False
690 if use_cache and not isinstance(past_key_values, Cache):
691 return_legacy_cache = True
692 if past_key_values is None:
693 past_key_values = DynamicCache()
694 else:
695 past_key_values = DynamicCache.from_legacy_cache(past_key_values)
696 logger.warning_once(
697 "We detected that you are passing `past_key_values` as a tuple of tuples. This is deprecated and "
698 "will be removed in v4.47. Please convert your cache or use an appropriate `Cache` class "
699 "(https://huggingface.co/docs/transformers/kv_cache#legacy-cache-format)"
700 )
701
702 seq_length = inputs_embeds.shape[1]
703 if cache_position is None:
704 past_seen_tokens = past_key_values.get_seq_length() if past_key_values is not None else 0
705 cache_position = torch.arange(past_seen_tokens, past_seen_tokens + seq_length, device=inputs_embeds.device)
706
707 if position_ids is None:
708 position_ids = cache_position.unsqueeze(0)
709
710 causal_mask = self._update_causal_mask(
711 attention_mask, inputs_embeds, cache_position, past_key_values, output_attentions
712 )
713
714 # Prepare head mask if needed
715 # 1.0 in head_mask indicate we keep the head
716 # attention_probs has shape bsz x num_heads x N x N
717 # head_mask has shape n_layer x batch x num_heads x N x N
718 head_mask = self.get_head_mask(head_mask, self.config.num_layers)
719 position_embeds = self.wpe(position_ids)
720 hidden_states = inputs_embeds + position_embeds
* Fix wrong inputs_embeds shape in doc
Supported by GPTNeoModel.forward, line 685--686:
src/transformers/models/gpt_neo/modeling_gpt_neo.py:
685 if inputs_embeds is None:
686 inputs_embeds = self.wte(input_ids)
* Fix wrong labels shape in doc
Supported by GPTNeoForCausalLM.forward, line 968--969:
src/transformers/models/gpt_neo/modeling_gpt_neo.py:
968 Labels for language modeling. Note that the labels **are shifted** inside the model, i.e. you can set
969 `labels = input_ids` Indices are selected in `[-100, 0, ..., config.vocab_size]` All labels set to `-100`
* Fix wrong position_ids shape in doc
Supported by FlaxGPTJPreTrainedModel.__call__, line 455--461:
src/transformers/models/gptj/modeling_flax_gptj.py:
455 batch_size, sequence_length = input_ids.shape
456
457 if position_ids is None:
458 if past_key_values is not None:
459 raise ValueError("Make sure to provide `position_ids` when passing `past_key_values`.")
460
461 position_ids = jnp.broadcast_to(jnp.arange(sequence_length)[None, :], (batch_size, sequence_length))
* Fix wrong token_type_ids shape in doc
Supported by TFGPTJMainLayer.call, line 482--493:
src/transformers/models/gptj/modeling_tf_gptj.py:
482 if inputs_embeds is None:
483 check_embeddings_within_bounds(input_ids, self.wte.vocab_size)
484 inputs_embeds = self.wte(input_ids, mode="embedding")
485
486 if token_type_ids is not None:
487 token_type_ids = tf.reshape(token_type_ids, [-1, shape_list(token_type_ids)[-1]])
488 token_type_embeds = self.wte(token_type_ids, mode="embedding")
489 else:
490 token_type_embeds = tf.constant(0.0)
491
492 token_type_embeds = tf.cast(token_type_embeds, dtype=inputs_embeds.dtype)
493 hidden_states = inputs_embeds + token_type_embeds
* Fix wrong position_ids shape in doc
Supported by TFGPTJMainLayer.call, line 434--449:
src/transformers/models/gptj/modeling_tf_gptj.py:
434 elif input_ids is not None:
435 input_shape = shape_list(input_ids)
436 input_ids = tf.reshape(input_ids, [-1, input_shape[-1]])
437 elif inputs_embeds is not None:
438 input_shape = shape_list(inputs_embeds)[:-1]
439 else:
440 raise ValueError("You have to specify either input_ids or inputs_embeds")
441
442 if past_key_values is None:
443 past_length = 0
444 past_key_values = [None] * len(self.h)
445 else:
446 past_length = shape_list(past_key_values[0][0])[-2]
447
448 if position_ids is None:
449 position_ids = tf.expand_dims(tf.range(past_length, input_shape[-1] + past_length), axis=0)
* Fix wrong inputs_embeds shape in doc
Supported by TFGPTJMainLayer.call, line 482--484:
src/transformers/models/gptj/modeling_tf_gptj.py:
482 if inputs_embeds is None:
483 check_embeddings_within_bounds(input_ids, self.wte.vocab_size)
484 inputs_embeds = self.wte(input_ids, mode="embedding")
* Fix wrong labels shape in doc
Supported by TFGPTJForCausalLM.call, line 812--813:
src/transformers/models/gptj/modeling_tf_gptj.py:
812 Labels for language modeling. Note that the labels **are shifted** inside the model, i.e. you can set
813 `labels = input_ids` Indices are selected in `[-100, 0, ..., config.vocab_size]` All labels set to `-100`
* Fix possibly wrong input_ids shape in doc
Since 'input_ids_length' was mentioned immediately after the shape `(batch_size, sequence_length)`, it doesn't make sense to me for `input_ids` to have such shape---IMO it ought to have shape `(batch_size, input_ids_length)` instead.
* Fix possibly wrong token_type_ids shape in doc
Supported by ImageGPTModel.forward, line 773--780:
src/transformers/models/imagegpt/modeling_imagegpt.py:
773 if inputs_embeds is None:
774 inputs_embeds = self.wte(input_ids)
775 position_embeds = self.wpe(position_ids)
776 hidden_states = inputs_embeds + position_embeds.to(inputs_embeds.device)
777
778 if token_type_ids is not None:
779 token_type_embeds = self.wte(token_type_ids)
780 hidden_states = hidden_states + token_type_embeds
This commit is introduced due to commit 8e594a4143cca79f165b99e4ed4c9f3a90047bf3.
* Fix possibly wrong position_ids shape in doc
Supported by ImageGPTModel.forward, line 773--776:
src/transformers/models/imagegpt/modeling_imagegpt.py:
773 if inputs_embeds is None:
774 inputs_embeds = self.wte(input_ids)
775 position_embeds = self.wpe(position_ids)
776 hidden_states = inputs_embeds + position_embeds.to(inputs_embeds.device)
This commit is introduced due to commit 8e594a4143cca79f165b99e4ed4c9f3a90047bf3.
* Fix possibly wrong inputs_embeds shape in doc
Supported by ImageGPTModel.forward, line 773--774:
src/transformers/models/imagegpt/modeling_imagegpt.py:
773 if inputs_embeds is None:
774 inputs_embeds = self.wte(input_ids)
This commit is introduced due to commit 8e594a4143cca79f165b99e4ed4c9f3a90047bf3.
* Fix possibly wrong labels shape in doc
Supported by ImageGPTForCausalImageModeling.forward, line 923--924:
src/transformers/models/imagegpt/modeling_imagegpt.py:
923 Labels for language modeling. Note that the labels **are shifted** inside the model, i.e. you can set
924 `labels = input_ids` Indices are selected in `[-100, 0, ..., config.vocab_size]` All labels set to `-100`
This commit is introduced due to commit 8e594a4143cca79f165b99e4ed4c9f3a90047bf3.
* Fix possibly wrong labels shape in doc
Supported by ImageGPTModel.forward, line 665--666:
src/transformers/models/imagegpt/modeling_imagegpt.py:
665 Labels for language modeling. Note that the labels **are shifted** inside the model, i.e. you can set
666 `labels = input_ids` Indices are selected in `[-100, 0, ..., config.vocab_size]` All labels set to `-100`
This commit is introduced due to commit 8e594a4143cca79f165b99e4ed4c9f3a90047bf3.
* Fix wrong position_ids shape in doc
Supported by FlaxLlamaPreTrainedModel.__call__, line 484--490:
src/transformers/models/llama/modeling_flax_llama.py:
484 batch_size, sequence_length = input_ids.shape
485
486 if position_ids is None:
487 if past_key_values is not None:
488 raise ValueError("Make sure to provide `position_ids` when passing `past_key_values`.")
489
490 position_ids = jnp.broadcast_to(jnp.arange(sequence_length)[None, :], (batch_size, sequence_length))
* Fix wrong position_ids shape in doc
Supported by FlaxMistralPreTrainedModel.__call__, line 478--484:
src/transformers/models/mistral/modeling_flax_mistral.py:
478 batch_size, sequence_length = input_ids.shape
479
480 if position_ids is None:
481 if past_key_values is not None:
482 raise ValueError("Make sure to provide `position_ids` when passing `past_key_values`.")
483
484 position_ids = jnp.broadcast_to(jnp.arange(sequence_length)[None, :], (batch_size, sequence_length))
* Fix qwen2_5 get_rope_index tensor device locations
* simpler fix
* edit right file for modular model
* add a test
* try normalizing type to fix non-video
* fix some imports
* add a video forward test with dummy input
* skip compilation on cpu offload
* add test
* better logic
* docstring
* boolean logic
* add disk offload check
* warn users if compilation options are set but compilation doesn happen
* fix test
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* fix: learning_rate logged as tensor causing save issue with deepspeed
* chore: lint
---------
Co-authored-by: NanoCode012 <chanvichet@Chanvichets-MacBook-Pro.local>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* Init `SinusoidsPositionEmbedding` with float to avoid precision problem
* fix hidden_state for talker
* Update modular_qwen2_5_omni.py
* Move hidden processing out from thinker
* fixup
---------
Co-authored-by: lvyuanjun.lyj <lvyuanjun.lyj@alibaba-inc.com>
* update aria tests
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* add cuda tests
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* check outputs for cpu and cuda and xpu
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* check outputs for cpu and cuda and xpu
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* check outputs for cpu and cuda and xpu
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* check output for each device
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* fix style
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* fix style
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* fix xpu output
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* add comments and use assert list equal
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* rm pad token assign
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
---------
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* fast image processor template for MobileNetV1 via transformers-cli
* Add fast image processors and unify tests for slow/fast image processor classes
* added loop over image_processor_list for all tests and removed boilerplate comments.
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* support poolformer fast image processor
* support test for crop_pct=None
* run make style
* Apply suggestions from code review
* rename test
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* tokenize inputs directly in apply_chat_template
* refactor processing
* revert changes processing llava
* Update docs
* fix issue with str being iterable
* add test chat text only
* change function name
- Since the `get_text_config` references an instance variable within
the class (`self.thinker_config`), the `get_text_config` method
should not be a classmethod.
- Before this fix, users were getting the following error:
'''
AttributeError: type object 'Qwen2_5OmniConfig' has no attribute 'thinker_config'
'''
* new card for mbart and mbart50
* removed comment BADGES
* Update mBart overview
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix typo (MBart to mBart)
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* maybe fix typo
* update typo and combine notes
* changed notes
* changed the example sentence
* fixed grammatical error and removed some lines from notes example
* missed one word
* removed documentation resources and added some lines of example code back in notes.
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* docs: ko: siglip.md
* feat: nmt draft
* fix: manual edits
* chore: Correct document title to kebab-case format
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Apply suggestions from code review
Convert unnatural language to natural Korean
Co-authored-by: Yijun Lee <119404328+yijun-lee@users.noreply.github.com>
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Yijun Lee <119404328+yijun-lee@users.noreply.github.com>
* enable blip2 and emu3 modeling cases on XPU
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* remove extra new line
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* update
---------
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
