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# coding=utf-8 # Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requir...
transformers/tests/models/bloom/test_modeling_bloom.py/0
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# coding=utf-8 # Copyright 2021 Google AI and HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by ...
transformers/tests/models/canine/test_tokenization_canine.py/0
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# coding=utf-8 # Copyright 2022 The OpenBMB Team and The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LIC...
transformers/tests/models/cpmant/test_modeling_cpmant.py/0
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# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/deberta/test_modeling_tf_deberta.py/0
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# coding=utf-8 # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/depth_anything/test_modeling_depth_anything.py/0
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# coding=utf-8 # Copyright 2021 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
transformers/tests/models/efficientformer/test_image_processing_efficientformer.py/0
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# coding=utf-8 # Copyright 2022 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
transformers/tests/models/glpn/test_image_processing_glpn.py/0
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# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/gpt_neox_japanese/test_modeling_gpt_neox_japanese.py/0
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# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/maskformer/test_modeling_maskformer_swin.py/0
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# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/mgp_str/test_processor_mgp_str.py/0
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# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/mra/test_modeling_mra.py/0
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# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/nat/test_modeling_nat.py/0
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# coding=utf-8 # Copyright 2023 IBM and HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unle...
transformers/tests/models/patchtsmixer/test_modeling_patchtsmixer.py/0
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# coding=utf-8 # Copyright 2023 Microsoft and the HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2....
transformers/tests/models/phi/test_modeling_phi.py/0
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# Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/models/pop2piano/test_processor_pop2piano.py/0
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# coding=utf-8 # Copyright 2020, The RAG Authors and The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/rag/test_modeling_rag.py/0
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# coding=utf-8 # Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/rembert/test_modeling_rembert.py/0
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# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/seamless_m4t/test_modeling_seamless_m4t.py/0
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# Copyright 2024 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/models/superpoint/test_modeling_superpoint.py/0
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# coding=utf-8 # Copyright 2018 Google T5 Authors and HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requ...
transformers/tests/models/t5/test_modeling_tf_t5.py/0
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# coding=utf-8 # Copyright 2021 HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law...
transformers/tests/models/vision_encoder_decoder/test_modeling_flax_vision_encoder_decoder.py/0
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# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/tests/models/vit_hybrid/test_modeling_vit_hybrid.py/0
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# Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/models/wav2vec2_with_lm/test_processor_wav2vec2_with_lm.py/0
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# coding=utf-8 # Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requir...
transformers/tests/models/xglm/test_tokenization_xglm.py/0
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# Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/pipelines/test_pipelines_table_question_answering.py/0
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# coding=utf-8 # Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless requir...
transformers/tests/quantization/autoawq/test_awq.py/0
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# we define a fixture function below and it will be "used" by # referencing its name from tests import os import pytest from attr import dataclass os.environ["AWS_DEFAULT_REGION"] = "us-east-1" # defaults region @dataclass class SageMakerTestEnvironment: framework: str role = "arn:aws:iam::558105141721:r...
transformers/tests/sagemaker/conftest.py/0
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# coding=utf-8 # Copyright 2023 HuggingFace Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
transformers/tests/test_image_processing_common.py/0
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# coding=utf-8 # Copyright 2018 HuggingFace Inc.. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or a...
transformers/tests/tokenization/test_tokenization_utils.py/0
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# Copyright 2020 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/trainer/test_data_collator.py/0
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# Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
transformers/tests/utils/test_dynamic_module_utils.py/0
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# coding=utf-8 # Copyright 2023 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/utils/check_build.py/0
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# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless r...
transformers/utils/create_dummy_models.py/0
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# coding=utf-8 # Copyright 2022 The HuggingFace Inc. team. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable...
transformers/utils/sort_auto_mappings.py/0
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# pip install openrlbenchmark==0.2.1a5 # see https://github.com/openrlbenchmark/openrlbenchmark#get-started for documentation echo "we deal with $TAGS_STRING" python -m openrlbenchmark.rlops_multi_metrics \ --filters '?we=huggingface&wpn=trl&xaxis=_step&ceik=trl_ppo_trainer_config.value.reward_model&cen=trl_ppo_tr...
trl/benchmark/benchmark_level2_plot.sh/0
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# Denoising Diffusion Policy Optimization ## The why | Before | After DDPO finetuning | | --- | --- | | <div style="text-align: center"><img src="https://huggingface.co/datasets/trl-internal-testing/example-images/resolve/main/images/pre_squirrel.png"/></div> | <div style="text-align: center"><img src="https://huggin...
trl/docs/source/ddpo_trainer.mdx/0
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# Reward Modeling TRL supports custom reward modeling for anyone to perform reward modeling on their dataset and model. Check out a complete flexible example at [`examples/scripts/reward_modeling.py`](https://github.com/huggingface/trl/tree/main/examples/scripts/reward_modeling.py). ## Expected dataset format The [...
trl/docs/source/reward_trainer.mdx/0
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import multiprocessing from dataclasses import dataclass, field from typing import Optional from datasets import load_dataset from transformers import AutoTokenizer, HfArgumentParser """ python -i examples/datasets/tokenize_ds.py --debug --model HuggingFaceH4/zephyr-7b-beta python -i examples/datasets/tokenize_ds.py...
trl/examples/datasets/tokenize_ds.py/0
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# Copyright 2023 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by appl...
trl/examples/research_projects/tools/calculator.py/0
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# Copyright 2023 metric-space, The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless require...
trl/tests/test_ddpo_trainer.py/0
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# This file is a copy of trl/examples/scripts/sft.py so that we could # use it together with rich and the TRL CLI in a more customizable manner. # Copyright 2024 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in comp...
trl/trl/commands/cli.py/0
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# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
trl/trl/trainer/base.py/0
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428
<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
accelerate/docs/source/basic_tutorials/install.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
accelerate/docs/source/index.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
accelerate/docs/source/usage_guides/big_modeling.md/0
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<!--Copyright 2022 The HuggingFace Team. All rights reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed...
accelerate/docs/source/usage_guides/training_zoo.md/0
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# Copyright 2021 The HuggingFace Inc. team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by appl...
accelerate/examples/complete_nlp_example.py/0
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#!/bin/bash #SBATCH --job-name=multigpu #SBATCH -D . #SBATCH --output=O-%x.%j #SBATCH --error=E-%x.%j #SBATCH --nodes=1 #SBATCH --ntasks-per-node=1 # number of MP tasks #SBATCH --gres=gpu:4 # number of GPUs per node #SBATCH --cpus-per-task=160 # number of cores per tasks #SBATCH --time=0...
accelerate/examples/slurm/submit_multigpu.sh/0
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#!/usr/bin/env python # Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unles...
accelerate/src/accelerate/commands/config/cluster.py/0
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#!/usr/bin/env python # Copyright 2021 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unles...
accelerate/src/accelerate/commands/test.py/0
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# Copyright 2023 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
accelerate/src/accelerate/utils/bnb.py/0
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# Copyright 2022 The HuggingFace Team. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicabl...
accelerate/src/accelerate/utils/torch_xla.py/0
{ "file_path": "accelerate/src/accelerate/utils/torch_xla.py", "repo_id": "accelerate", "token_count": 691 }
9
compute_environment: LOCAL_MACHINE deepspeed_config: {} distributed_type: 'NO' downcast_bf16: 'no' fsdp_config: {} gpu_ids: all machine_rank: 0 main_process_ip: null main_process_port: null main_training_function: main megatron_lm_config: {} mixed_precision: 'no' num_machines: 1 num_processes: 1 rdzv_backend: static sa...
accelerate/tests/test_configs/latest.yaml/0
{ "file_path": "accelerate/tests/test_configs/latest.yaml", "repo_id": "accelerate", "token_count": 186 }
10
# Model arguments model_name_or_path: HuggingFaceH4/starchat2-15b-sft-v0.1 torch_dtype: bfloat16 # Data training arguments # For definitions, see: src/h4/training/config.py dataset_mixer: HuggingFaceH4/ultrafeedback_binarized: 1.0 HuggingFaceH4/orca_dpo_pairs: 1.0 dataset_splits: - train_prefs - test_prefs preproc...
alignment-handbook/recipes/starchat2-15b/dpo/config_v0.1.yaml/0
{ "file_path": "alignment-handbook/recipes/starchat2-15b/dpo/config_v0.1.yaml", "repo_id": "alignment-handbook", "token_count": 399 }
11
__version__ = "0.3.0.dev0" from .configs import DataArguments, DPOConfig, H4ArgumentParser, ModelArguments, SFTConfig from .data import apply_chat_template, get_datasets from .decontaminate import decontaminate_humaneval from .model_utils import ( get_checkpoint, get_kbit_device_map, get_peft_config, g...
alignment-handbook/src/alignment/__init__.py/0
{ "file_path": "alignment-handbook/src/alignment/__init__.py", "repo_id": "alignment-handbook", "token_count": 148 }
12
# Creating a desktop Tauri app
candle/candle-book/src/apps/desktop.md/0
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13
#[cfg(test)] pub mod simplified; #[cfg(test)] mod tests { use anyhow::Result; use candle::{DType, Device, Tensor}; use parquet::file::reader::SerializedFileReader; // NOTE: Waiting on https://github.com/rust-lang/mdBook/pull/1856 #[rustfmt::skip] #[tokio::test] async fn book_hub_1() { // A...
candle/candle-book/src/lib.rs/0
{ "file_path": "candle/candle-book/src/lib.rs", "repo_id": "candle", "token_count": 2806 }
14
#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use anyhow::Result; use candle_core::{Device, Tensor}; fn main() -> Result<()> { let a = Tensor::new(&[[0.0f32, 1.0, 2.0], [3.0, 4.0, 5.0]], &Device::Cpu)?; let b = Tensor::new(&[[88.0f32, 99.0]], ...
candle/candle-core/examples/basics.rs/0
{ "file_path": "candle/candle-core/examples/basics.rs", "repo_id": "candle", "token_count": 287 }
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use crate::backend::{BackendDevice, BackendStorage}; use crate::op::{BinaryOpT, CmpOp, ReduceOp, UnaryOpT}; use crate::{CpuStorage, DType, Layout, Result, Shape, WithDType}; pub use candle_kernels as kernels; pub use cudarc; use cudarc::cublas::{Gemm, GemmConfig, StridedBatchedConfig}; use cudarc::driver::{ CudaFun...
candle/candle-core/src/cuda_backend.rs/0
{ "file_path": "candle/candle-core/src/cuda_backend.rs", "repo_id": "candle", "token_count": 47475 }
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use super::k_quants::{ BlockQ2K, BlockQ3K, BlockQ4K, BlockQ4_0, BlockQ5K, BlockQ6K, BlockQ8K, BlockQ8_0, QK8_0, QK_K, }; use crate::Result; use byteorder::{ByteOrder, LittleEndian}; use half::f16; #[cfg(target_arch = "x86")] use core::arch::x86::*; #[cfg(target_arch = "x86_64")] use core::arch::x86_64::*; #[inlin...
candle/candle-core/src/quantized/avx.rs/0
{ "file_path": "candle/candle-core/src/quantized/avx.rs", "repo_id": "candle", "token_count": 17495 }
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use crate::Layout; /// An iterator over offset position for items of an N-dimensional arrays stored in a /// flat buffer using some potential strides. #[derive(Debug)] pub struct StridedIndex<'a> { next_storage_index: Option<usize>, multi_index: Vec<usize>, dims: &'a [usize], stride: &'a [usize], } im...
candle/candle-core/src/strided_index.rs/0
{ "file_path": "candle/candle-core/src/strided_index.rs", "repo_id": "candle", "token_count": 1148 }
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/// Regression test for pth files not loading on Windows. #[test] fn test_pth() { let tensors = candle_core::pickle::PthTensors::new("tests/test.pt", None).unwrap(); tensors.get("test").unwrap().unwrap(); } #[test] fn test_pth_with_key() { let tensors = candle_core::pickle::PthTensors::new("tests/t...
candle/candle-core/tests/pth_tests.rs/0
{ "file_path": "candle/candle-core/tests/pth_tests.rs", "repo_id": "candle", "token_count": 440 }
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//! The MNIST hand-written digit dataset. //! //! The files can be obtained from the following link: //! <http://yann.lecun.com/exdb/mnist/> use candle::{DType, Device, Error, Result, Tensor}; use hf_hub::{api::sync::Api, Repo, RepoType}; use parquet::file::reader::{FileReader, SerializedFileReader}; use std::fs::File;...
candle/candle-datasets/src/vision/mnist.rs/0
{ "file_path": "candle/candle-datasets/src/vision/mnist.rs", "repo_id": "candle", "token_count": 2129 }
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#include <stdint.h> #include "reduction_utils.cuh" template <typename scalar_t> __device__ void rms_norm_kernel(scalar_t *__restrict__ out, // [num_tokens, hidden_size] const scalar_t *__restrict__ input, // [num_tokens, hidden_size] const float epsilon, const uint32_t num_token...
candle/candle-examples/examples/custom-ops/kernels/layernorm_kernels.cu/0
{ "file_path": "candle/candle-examples/examples/custom-ops/kernels/layernorm_kernels.cu", "repo_id": "candle", "token_count": 561 }
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# candle-gemma: 2b and 7b LLMs from Google DeepMind [Gemma](https://ai.google.dev/gemma/docs) is a collection of lightweight open models published by Google Deepmind with a 2b and a 7b variant. In order to use the example below, you have to accept the license on the [HuggingFace Hub Gemma repo](https://huggingface.co...
candle/candle-examples/examples/gemma/README.md/0
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use anyhow::Error as E; use clap::{Parser, ValueEnum}; use candle::{DType, Tensor}; use candle_examples::token_output_stream::TokenOutputStream; use candle_nn::VarBuilder; use candle_transformers::models::...
candle/candle-examples/examples/marian-mt/main.rs/0
{ "file_path": "candle/candle-examples/examples/marian-mt/main.rs", "repo_id": "candle", "token_count": 2385 }
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use anyhow::{Error as E, Result}; use clap::{Parser, ValueEnum}; use candle_transformers::models::mixformer::{Config, MixFormerSequentialForCausalLM as MixFormer}; use candle_transformers::models::phi::{Co...
candle/candle-examples/examples/phi/main.rs/0
{ "file_path": "candle/candle-examples/examples/phi/main.rs", "repo_id": "candle", "token_count": 8133 }
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use anyhow::{Error as E, Result}; use clap::Parser; use candle_transformers::models::mpt::{Config, Model as M}; use candle_transformers::models::quantized_mpt::Model as Q; use candle::{DType, Device, Tens...
candle/candle-examples/examples/replit-code/main.rs/0
{ "file_path": "candle/candle-examples/examples/replit-code/main.rs", "repo_id": "candle", "token_count": 3752 }
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# candle-stable-diffusion: A Diffusers API in Rust/Candle ![rusty robot holding a candle](./assets/stable-diffusion-xl.jpg) _A rusty robot holding a fire torch in its hand_, generated by Stable Diffusion XL using Rust and [candle](https://github.com/huggingface/candle). The `stable-diffusion` example is a conversion...
candle/candle-examples/examples/stable-diffusion/README.md/0
{ "file_path": "candle/candle-examples/examples/stable-diffusion/README.md", "repo_id": "candle", "token_count": 917 }
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use candle_transformers::object_detection::{non_maximum_suppression, Bbox}; mod darknet; use anyhow::Result; use candle::{DType, Device, Tensor}; use candle_nn::{Module, VarBuilder}; use clap::Parser; use ...
candle/candle-examples/examples/yolo-v3/main.rs/0
{ "file_path": "candle/candle-examples/examples/yolo-v3/main.rs", "repo_id": "candle", "token_count": 3180 }
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[package] name = "candle-flash-attn" version = "0.4.2" edition = "2021" description = "Flash attention layer for the candle ML framework." repository = "https://github.com/huggingface/candle" keywords = ["blas", "tensor", "machine-learning"] categories = ["science"] license = "MIT OR Apache-2.0" readme = "README.md" ...
candle/candle-flash-attn/Cargo.toml/0
{ "file_path": "candle/candle-flash-attn/Cargo.toml", "repo_id": "candle", "token_count": 266 }
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mod ffi; use candle::backend::BackendStorage; use candle::cuda_backend::cudarc::driver::DevicePtr; use candle::cuda_backend::WrapErr; use candle::{CpuStorage, DType, Layout, Result, Shape, Tensor}; use half::{bf16, f16}; pub struct FlashAttn { pub softmax_scale: f32, pub alibi_slopes: Option<Tensor>, pub ...
candle/candle-flash-attn/src/lib.rs/0
{ "file_path": "candle/candle-flash-attn/src/lib.rs", "repo_id": "candle", "token_count": 15951 }
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#include "cuda_utils.cuh" #include <cmath> #include <stdint.h> const int BLOCK_SIZE = 1024; // TODO: Maybe add some fast_sum_f16_f32 variant that not only accumulate in f32 // but also expect a f32 output so that this can be used for normalization e.g. // in softmax. // Fast reduce sum kernel, this assumes that the ...
candle/candle-kernels/src/reduce.cu/0
{ "file_path": "candle/candle-kernels/src/reduce.cu", "repo_id": "candle", "token_count": 8419 }
30
use super::*; use half::{bf16, f16}; use metal::MTLResourceOptions; fn read_to_vec<T: Clone>(buffer: &Buffer, n: usize) -> Vec<T> { let ptr = buffer.contents() as *const T; assert!(!ptr.is_null()); let slice = unsafe { std::slice::from_raw_parts(ptr, n) }; slice.to_vec() } fn new_buffer<T>(device: &De...
candle/candle-metal-kernels/src/tests.rs/0
{ "file_path": "candle/candle-metal-kernels/src/tests.rs", "repo_id": "candle", "token_count": 29021 }
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//! Group Normalization. //! //! This layer applies Group Normalization over a mini-batch of inputs. use candle::{DType, Result, Tensor}; // This group norm version handles both weight and bias so removes the mean. #[derive(Clone, Debug)] pub struct GroupNorm { weight: Tensor, bias: Tensor, eps: f64, n...
candle/candle-nn/src/group_norm.rs/0
{ "file_path": "candle/candle-nn/src/group_norm.rs", "repo_id": "candle", "token_count": 1372 }
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use candle::{Result, Shape, Tensor}; use candle_nn::encoding::one_hot; #[test] fn test_i64_one_hot() -> Result<()> { let device = candle::Device::Cpu; let indices = Tensor::new(vec![vec![0i64, 2], vec![1, -1]], &device)?; let depth = 4; let on_value = 1.0; let off_value = 0.0; let one_hot = ...
candle/candle-nn/tests/one_hot.rs/0
{ "file_path": "candle/candle-nn/tests/one_hot.rs", "repo_id": "candle", "token_count": 1592 }
33
fn main() { pyo3_build_config::add_extension_module_link_args(); }
candle/candle-pyo3/build.rs/0
{ "file_path": "candle/candle-pyo3/build.rs", "repo_id": "candle", "token_count": 30 }
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import candle from candle import Tensor _UNSIGNED_DTYPES = set([str(candle.u8), str(candle.u32)]) def _assert_tensor_metadata( actual: Tensor, expected: Tensor, check_device: bool = True, check_dtype: bool = True, check_layout: bool = True, check_stride: bool = False, ): if check_device:...
candle/candle-pyo3/py_src/candle/testing/__init__.py/0
{ "file_path": "candle/candle-pyo3/py_src/candle/testing/__init__.py", "repo_id": "candle", "token_count": 854 }
35
import candle from candle import Tensor from candle.testing import assert_equal, assert_almost_equal import pytest @pytest.mark.parametrize("dtype", [candle.f32, candle.f64, candle.f16, candle.u32, candle.u8, candle.i64]) def test_assert_equal_asserts_correctly(dtype: candle.DType): a = Tensor([1, 2, 3]).to(dtype...
candle/candle-pyo3/tests/bindings/test_testing.py/0
{ "file_path": "candle/candle-pyo3/tests/bindings/test_testing.py", "repo_id": "candle", "token_count": 476 }
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use super::with_tracing::{layer_norm, linear, LayerNorm, Linear}; use candle::{DType, Device, Result, Tensor}; use candle_nn::{Embedding, Module, VarBuilder}; use serde::Deserialize; pub const DTYPE: DType = DType::F32; fn masked_fill(on_false: &Tensor, mask: &Tensor, on_true: f32) -> Result<Tensor> { let shape =...
candle/candle-transformers/src/models/distilbert.rs/0
{ "file_path": "candle/candle-transformers/src/models/distilbert.rs", "repo_id": "candle", "token_count": 5381 }
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//! MobileOne inference implementation based on timm and candle-repvgg //! //! See "MobileOne: An Improved One millisecond Mobile Backbone" //! https://arxiv.org/abs/2206.04040 use candle::{DType, Result, Tensor, D}; use candle_nn::{ batch_norm, conv2d, conv2d_no_bias, linear, ops::sigmoid, BatchNorm, Conv2d, Conv...
candle/candle-transformers/src/models/mobileone.rs/0
{ "file_path": "candle/candle-transformers/src/models/mobileone.rs", "repo_id": "candle", "token_count": 4721 }
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// T5 Text Model, quantized version // https://github.com/huggingface/transformers/blob/main/src/transformers/models/t5/modeling_t5.py use crate::models::t5::{deserialize_feed_forward_proj_activation, ActivationWithOptionalGating}; use crate::models::with_tracing::QMatMul; use crate::quantized_nn::Embedding; pub use c...
candle/candle-transformers/src/models/quantized_t5.rs/0
{ "file_path": "candle/candle-transformers/src/models/quantized_t5.rs", "repo_id": "candle", "token_count": 13996 }
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//! # Denoising Diffusion Implicit Models //! //! The Denoising Diffusion Implicit Models (DDIM) is a simple scheduler //! similar to Denoising Diffusion Probabilistic Models (DDPM). The DDPM //! generative process is the reverse of a Markovian process, DDIM generalizes //! this to non-Markovian guidance. //! //! Denoi...
candle/candle-transformers/src/models/stable_diffusion/ddim.rs/0
{ "file_path": "candle/candle-transformers/src/models/stable_diffusion/ddim.rs", "repo_id": "candle", "token_count": 3953 }
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use crate::models::with_tracing::{conv2d, linear, linear_no_bias, Conv2d, Linear}; use candle::{IndexOp, Module, Result, Tensor, D}; use candle_nn::{layer_norm, LayerNorm, VarBuilder}; // https://github.com/huggingface/transformers/blob/main/src/transformers/models/vit/configuration_vit.py #[derive(Debug, Clone, serde...
candle/candle-transformers/src/models/vit.rs/0
{ "file_path": "candle/candle-transformers/src/models/vit.rs", "repo_id": "candle", "token_count": 5870 }
41
use candle::{DType, Device, IndexOp, Result, Tensor, D}; use candle_nn::{ embedding, linear_no_bias as linear, rms_norm, Embedding, Linear, Module, RmsNorm, VarBuilder, }; use std::collections::HashMap; use std::sync::{Arc, Mutex}; #[derive(Debug, Clone)] pub struct Config { pub dim: usize, // transform...
candle/candle-wasm-examples/llama2-c/src/model.rs/0
{ "file_path": "candle/candle-wasm-examples/llama2-c/src/model.rs", "repo_id": "candle", "token_count": 5272 }
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use crate::console_log; use crate::worker::{ModelData, Segment, Worker, WorkerInput, WorkerOutput}; use js_sys::Date; use wasm_bindgen::prelude::*; use wasm_bindgen_futures::JsFuture; use yew::{html, Component, Context, Html}; use yew_agent::{Bridge, Bridged}; const SAMPLE_NAMES: [&str; 6] = [ "audios/samples_jfk....
candle/candle-wasm-examples/whisper/src/app.rs/0
{ "file_path": "candle/candle-wasm-examples/whisper/src/app.rs", "repo_id": "candle", "token_count": 5679 }
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use candle_wasm_example_yolo::coco_classes; use candle_wasm_example_yolo::model::Bbox; use candle_wasm_example_yolo::worker::Model as M; use candle_wasm_example_yolo::worker::ModelPose as P; use wasm_bindgen::prelude::*; #[wasm_bindgen] pub struct Model { inner: M, } #[wasm_bindgen] impl Model { #[wasm_bindge...
candle/candle-wasm-examples/yolo/src/bin/m.rs/0
{ "file_path": "candle/candle-wasm-examples/yolo/src/bin/m.rs", "repo_id": "candle", "token_count": 840 }
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# template used in production for HuggingChat. MODELS=`[ { "name" : "mistralai/Mixtral-8x7B-Instruct-v0.1", "description" : "The latest MoE model from Mistral AI! 8x7B and outperforms Llama 2 70B in most benchmarks.", "logoUrl": "https://huggingface.co/datasets/huggingchat/models-logo/resolve/main/mist...
chat-ui/.env.template/0
{ "file_path": "chat-ui/.env.template", "repo_id": "chat-ui", "token_count": 5847 }
45
import readline from "readline"; import minimist from "minimist"; // @ts-expect-error: vite-node makes the var available but the typescript compiler doesn't see them import { MONGODB_URL } from "$env/static/private"; import { faker } from "@faker-js/faker"; import { ObjectId } from "mongodb"; import { collections } ...
chat-ui/scripts/populate.ts/0
{ "file_path": "chat-ui/scripts/populate.ts", "repo_id": "chat-ui", "token_count": 3340 }
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<script lang="ts"> export let isCollapsed: boolean; export let classNames: string; </script> <button on:click class="{classNames} group flex h-16 w-6 flex-col items-center justify-center -space-y-1 outline-none *:h-3 *:w-1 *:rounded-full *:hover:bg-gray-300 max-md:hidden dark:*:hover:bg-gray-600 {!isCollapsed ? ...
chat-ui/src/lib/components/ExpandNavigation.svelte/0
{ "file_path": "chat-ui/src/lib/components/ExpandNavigation.svelte", "repo_id": "chat-ui", "token_count": 238 }
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<script lang="ts"> import { fade } from "svelte/transition"; import IconDazzled from "$lib/components/icons/IconDazzled.svelte"; export let message = ""; </script> <div transition:fade|global={{ duration: 300 }} class="pointer-events-none fixed right-0 top-12 z-20 bg-gradient-to-bl from-red-500/20 via-red-500/0...
chat-ui/src/lib/components/Toast.svelte/0
{ "file_path": "chat-ui/src/lib/components/Toast.svelte", "repo_id": "chat-ui", "token_count": 259 }
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<script lang="ts"> import { page } from "$app/stores"; import { PUBLIC_APP_ASSETS, PUBLIC_APP_NAME, PUBLIC_ORIGIN } from "$env/static/public"; import { base } from "$app/paths"; export let classNames = ""; </script> {#if PUBLIC_APP_ASSETS === "chatui"} <svg height="30" width="30" viewBox="0 0 30 30" xmln...
chat-ui/src/lib/components/icons/Logo.svelte/0
{ "file_path": "chat-ui/src/lib/components/icons/Logo.svelte", "repo_id": "chat-ui", "token_count": 550 }
49
import { z } from "zod"; import { ANTHROPIC_API_KEY } from "$env/static/private"; import type { Endpoint } from "../endpoints"; import type { TextGenerationStreamOutput } from "@huggingface/inference"; export const endpointAnthropicParametersSchema = z.object({ weight: z.number().int().positive().default(1), model: ...
chat-ui/src/lib/server/endpoints/anthropic/endpointAnthropic.ts/0
{ "file_path": "chat-ui/src/lib/server/endpoints/anthropic/endpointAnthropic.ts", "repo_id": "chat-ui", "token_count": 1031 }
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import { dot } from "@xenova/transformers"; import type { EmbeddingBackendModel } from "$lib/server/embeddingModels"; import type { Embedding } from "$lib/server/embeddingEndpoints/embeddingEndpoints"; // see here: https://github.com/nmslib/hnswlib/blob/359b2ba87358224963986f709e593d799064ace6/README.md?plain=1#L34 fu...
chat-ui/src/lib/server/sentenceSimilarity.ts/0
{ "file_path": "chat-ui/src/lib/server/sentenceSimilarity.ts", "repo_id": "chat-ui", "token_count": 497 }
51
import { writable } from "svelte/store"; export interface WebSearchParameters { useSearch: boolean; nItems: number; } export const webSearchParameters = writable<WebSearchParameters>({ useSearch: false, nItems: 5, });
chat-ui/src/lib/stores/webSearchParameters.ts/0
{ "file_path": "chat-ui/src/lib/stores/webSearchParameters.ts", "repo_id": "chat-ui", "token_count": 68 }
52
import type { Conversation } from "./Conversation"; export type SharedConversation = Pick< Conversation, | "model" | "embeddingModel" | "title" | "rootMessageId" | "messages" | "preprompt" | "assistantId" | "createdAt" | "updatedAt" > & { _id: string; hash: string; };
chat-ui/src/lib/types/SharedConversation.ts/0
{ "file_path": "chat-ui/src/lib/types/SharedConversation.ts", "repo_id": "chat-ui", "token_count": 114 }
53
import type { Conversation } from "$lib/types/Conversation"; import { sha256 } from "./sha256"; export async function hashConv(conv: Conversation) { // messages contains the conversation message but only the immutable part const messages = conv.messages.map((message) => { return (({ from, id, content, webSearchId ...
chat-ui/src/lib/utils/hashConv.ts/0
{ "file_path": "chat-ui/src/lib/utils/hashConv.ts", "repo_id": "chat-ui", "token_count": 132 }
54
import { collections } from "$lib/server/database"; import { ObjectId } from "mongodb"; import { describe, expect, it } from "vitest"; import { insertLegacyConversation, insertSideBranchesConversation } from "./treeHelpers.spec"; import type { Message } from "$lib/types/Message"; import { addSibling } from "./addSibli...
chat-ui/src/lib/utils/tree/addSibling.spec.ts/0
{ "file_path": "chat-ui/src/lib/utils/tree/addSibling.spec.ts", "repo_id": "chat-ui", "token_count": 950 }
55
import { collections } from "$lib/server/database"; import { authCondition } from "$lib/server/auth"; import type { Conversation } from "$lib/types/Conversation"; export async function GET({ locals }) { if (locals.user?._id || locals.sessionId) { const convs = await collections.conversations .find({ ...authC...
chat-ui/src/routes/api/conversations/+server.ts/0
{ "file_path": "chat-ui/src/routes/api/conversations/+server.ts", "repo_id": "chat-ui", "token_count": 298 }
56
import { authCondition } from "$lib/server/auth"; import { collections } from "$lib/server/database"; import type { SharedConversation } from "$lib/types/SharedConversation"; import { getShareUrl } from "$lib/utils/getShareUrl"; import { hashConv } from "$lib/utils/hashConv"; import { error } from "@sveltejs/kit"; impo...
chat-ui/src/routes/conversation/[id]/share/+server.ts/0
{ "file_path": "chat-ui/src/routes/conversation/[id]/share/+server.ts", "repo_id": "chat-ui", "token_count": 761 }
57