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  • 8c12690cec [Grounding DINO] Add resources (#30232) * Add resources * Address comments * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
  • d2cec09baa Add TF swiftformer (#23342) * 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: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Remove FIXME comment * Remove from_pt * Update copyright year Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Rename one-letter variables * Remove FIXMEs related to momentum * Remove old TODO comment * Remove outstanding FIXME comments * Get dropout rate from config * Add specific dropout config for MLP * Add convencoder dropout to config * Pass config to SwiftFormerDropPath layer * Fix drop_path variable name and add Adapted from comment * Run ruff * Removed copied from comment * Run fix copies * Change drop_path to identity to match pt * Cleanup build() methods and move to new keras imports * Update docs/source/en/model_doc/swiftformer.md 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@users.noreply.github.com> * Remove drop_path function * Add training to TFSwiftFormerEncoder * Set self.built = True last Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Should have been added to previous commit Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Apply suggestions from code review Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Change default_feature_extractor to default_image_processor Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> * Import Keras from modeling_tf_utils * Remove relative import * Run ruff --fix * Move import keras to tf_available * Add copied from comment to test_forward_signature * Reduce batch size and num_labels * Extract loss logic to hf_compute_loss * Run ruff format --------- Co-authored-by: Matt <rocketknight1@gmail.com> Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
  • 21c912e79c Fix config + attn_implementation in AutoModelForCausalLM.from_pretrained (#30299) * Update modeling_utils.py * Update test_modeling_utils.py * Update test_modeling_utils.py * Update test_modeling_utils.py
  • b1cd48740e Do not remove half seq length in generation tests (#30016) * 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: Arthur <48595927+ArthurZucker@users.noreply.github.com> * [test all] remove unused variables --------- Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
  • b4fd49b6c5 Update unwrap from accelerate (#29933) * Use unwrap with the one in accelerate * oups * update unwrap * fix * wording * raise error instead * comment * doc * Update src/transformers/modeling_utils.py Co-authored-by: Zach Mueller <muellerzr@gmail.com> * style * put else --------- Co-authored-by: Zach Mueller <muellerzr@gmail.com>
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  • 5a4b9cade6 VeRA (Vector Based Random Matrix Adaption) (#1564) Implements VeRA: https://huggingface.co/papers/2310.11454 VeRA is similar to LoRA but even more parameter efficient, while promising to keep the same performance. In its current implementation, it has a few limitations compared to LoRA: - All targeted parameters must have the same shape. - Only `nn.Linear` layers are supported. - Quantized layers are not supported. This PR is based on, and supersedes, #1039. --------- Co-authored-by: Alex McKinney <alex.f.mckinney@gmail.com> Co-authored-by: Dawid <20214809+dkopi@users.noreply.github.com>

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  • dce03862d5 feat(model): Support Qwen2MoE (#1439) Co-authored-by: Fangyin Cheng <staneyffer@gmail.com>
  • 82e4ce4c43 feat(model): Support Llama-3 (#1436)
  • b49b07f011 feat[Datasource]:add summary refresh (#1433) Co-authored-by: hzh97 <2976151305@qq.com>
  • 57be1ece18 feat(core): Upgrade pydantic to 2.x (#1428)
  • baa1e3f9f6 fix:[chatdb] clickhouse occur error AttributeError: 'ClickhouseConnect… (#1432)
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  • 40398976f6 [paddle-pipelines] faq semantic search question answering reamde (#8292) * Update dense qa readme * Update readme * Update semantic search readme

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  • 6e0e6e752f * fix several bugs (#301) * * fix for "undefined opencc" bug for chinese_convert_mapper * * allow to change the config of opencc converter * * fix: undefined punctuation_pattern

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  • 9977dea982 deploy: 6e0e6e752fe4aaf3079b2b94536c4a0588dbb8a1

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  • 54a679474a [Serving] Support ThreadedEngine Reload/Unload/Reset (#2185) This PR brings the support of reload (reload the engine with a new model), unload (unload the current running model) and reset (reset the engine to the initial states without unloading) to ThreadedEngine and JSONFFIEngine. These functions are useful for app bindings for iOS/Android.
  • d43e10e67c [Serving][Spec] Fix the output inconsistent bug of q0f32 spec decoding (#2184) - According to https://github.com/mlc-ai/mlc-llm/issues/2167, the problem that the output of spec decoding in q0f32 is inconsistent with the single model of q0f32 has been fixed. - Modified the test_engine_generate function located in `tests/python/serve/test_serve_engine_spec.py` to support comparison of the output of a single model and the output of spec decoding - The accuracy comparison with hugging face is left (because the current version of llama-2-7b of q0f32 cannot be consistent with the output of hugging face model) - The output of spec decoding for q0f16 cannot be consistent with the output of a single model of q0f16, but this may be due to floating point errors. Co-authored-by: DearFishi <yw6m20@soton.ac.u>
  • 132ad03077 Change OpenAI protocol default value to None and supply using model config (#2178) * Change OpenAI protocol default value to None and supply using model config * Fix lint
  • 0ec6c7aa93 [Misc] Pass env along when calling `subprocess.run` (#2179) The uses of `subprocess.run` in the codebase did not pass the environment, which may cause some issues in cases.
  • 675319f2ee [Docs] Update project website (#2180) This PR updates the project landing website to remove some information.
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  • cc74b2b232 Updating lm-format-enforcer version and adding links to decoding libraries in docs (#4222)
  • 91528575ec [Frontend] multiple sampling params support (#3570)
  • a22cdea371 [Kernel][FP8] Initial support with dynamic per-tensor scaling (#4118) Provide an initial support to FP8 computation. This PR is inspired by HuggingFace TGI: huggingface/text-generation-inference#1726 This feature can be enabled with --quantization fp8 or -q fp8 when launching an engine. Algorithm: We still load a model checkpoint in FP16/BF16. After the weights are loaded, Fp8LinearMethod calculates the per-tensor scaling factor of weights and quantizes the weights accordingly. The scaling factor will then be stored for future use. Meanwhile, the per-tensor scaling factor for activations is calculated in every forward pass. Initial Results: Currently tested Mistral-7B on 1xH100. With prompt length ~5 and decoding length 128: BF16: 1.47s FP8: 1.66s I'll try to use larger models and try to find more performance bottleneck. Meanwhile, you're welcome to try this code.
  • 682789d402 Fix missing docs and out of sync `EngineArgs` (#4219) Co-authored-by: Harry Mellor <hmellor@oxts.com>
  • 138485a82d [Bugfix] Add fix for JSON whitespace (#4189) Co-authored-by: Ubuntu <ubuntu@ip-172-31-13-147.ec2.internal>
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