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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/poolformer/test_image_processing_poolformer.py/0
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# coding=utf-8 # Copyright 2024 The Qwen team, Alibaba Group 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/...
transformers/tests/models/qwen2/test_modeling_qwen2.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/regnet/test_modeling_regnet.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...
transformers/tests/models/roberta_prelayernorm/test_modeling_flax_roberta_prelayernorm.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/sam/test_processor_sam.py/0
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397
# 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/swin2sr/test_image_processing_swin2sr.py/0
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398
# coding=utf-8 # Copyright 2023 The Intel Team Authors, 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/...
transformers/tests/models/tvp/test_modeling_tvp.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/vilt/test_image_processing_vilt.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/x_clip/test_modeling_x_clip.py/0
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401
# coding=utf-8 # 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 requir...
transformers/tests/models/xlm_roberta/test_modeling_xlm_roberta.py/0
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# coding=utf-8 # 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 requir...
transformers/tests/optimization/test_optimization.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/pipelines/test_pipelines_mask_generation.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/pipelines/test_pipelines_zero_shot_object_detection.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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408
# 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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411
# 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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412
# 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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413
# pip install openrlbenchmark==0.2.1a5 # see https://github.com/openrlbenchmark/openrlbenchmark#get-started for documentation BASELINE_PR_TAG=v0.4.7-55-g110e672 BASELINE_PR_NAME=PR-662 python -m openrlbenchmark.rlops_multi_metrics \ --filters '?we=huggingface&wpn=trl&xaxis=_step&ceik=trl_ppo_trainer_config.value.r...
trl/benchmark/plot.sh/0
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# Examples ## Introduction The examples should work in any of the following settings (with the same script): - single GPU - multi GPUS (using PyTorch distributed mode) - multi GPUS (using DeepSpeed ZeRO-Offload stages 1, 2, & 3) - fp16 (mixed-precision), fp32 (normal precision), or bf16 (bfloat16 precisi...
trl/docs/source/example_overview.md/0
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# Trainer At TRL we support PPO (Proximal Policy Optimisation) with an implementation that largely follows the structure introduced in the paper "Fine-Tuning Language Models from Human Preferences" by D. Ziegler et al. [[paper](https://arxiv.org/pdf/1909.08593.pdf), [code](https://github.com/openai/lm-human-preferenc...
trl/docs/source/trainer.mdx/0
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from dataclasses import dataclass, field from typing import Optional import torch from peft import PeftConfig, PeftModel from transformers import AutoModelForCausalLM, AutoModelForSequenceClassification, AutoTokenizer, HfArgumentParser @dataclass class ScriptArguments: """ The input names representing the Ad...
trl/examples/research_projects/stack_llama/scripts/merge_peft_adapter.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...
trl/examples/scripts/ppo.py/0
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import unittest import torch from transformers import AutoTokenizer, GenerationConfig from trl import AutoModelForCausalLMWithValueHead from trl.core import LengthSampler from trl.extras import BestOfNSampler def queries_to_scores(list_of_strings): return [torch.rand(1).item() for _ in list_of_strings] class ...
trl/tests/test_best_of_n_sampler.py/0
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419
# 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...
trl/tests/testing_utils.py/0
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420
import os import sys import warnings from dataclasses import dataclass, field from typing import Literal, Optional from ..core import flatten_dict from ..import_utils import is_bitsandbytes_available, is_torchvision_available @dataclass class DDPOConfig: """ Configuration class for DDPOTrainer """ #...
trl/trl/trainer/ddpo_config.py/0
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421
import gc import threading import time import psutil import torch class PeakCPUMemory: def __init__(self): self.process = psutil.Process() self.peak_monitoring = False def peak_monitor(self): self.cpu_memory_peak = -1 while True: self.cpu_memory_peak = max(self.p...
accelerate/benchmarks/measures_util.py/0
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0
<!--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 applicable law or agreed...
accelerate/docs/source/concept_guides/low_precision_training.md/0
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1
<!--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 applicable law or agreed...
accelerate/docs/source/package_reference/torch_wrappers.md/0
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2
<!--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/mps.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 applicabl...
accelerate/manim_animations/big_model_inference/stage_1.py/0
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4
#!/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/config.py/0
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#!/usr/bin/env python # 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 # # Unles...
accelerate/src/accelerate/commands/tpu.py/0
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6
# 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...
accelerate/src/accelerate/test_utils/scripts/external_deps/test_peak_memory_usage.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/environment.py/0
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{ "fp16": { "enabled": "auto", "loss_scale": 0, "loss_scale_window": 1000, "initial_scale_power": 16, "hysteresis": 2, "min_loss_scale": 1 }, "bf16": { "enabled": "auto" }, "optimizer": { "type": "AdamW", "params": { ...
accelerate/tests/deepspeed/ds_config_zero2.json/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/tests/test_hooks.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/tests/test_tracking.py/0
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#!/bin/bash #SBATCH --ntasks-per-node=1 #SBATCH --exclusive #SBATCH --gres=gpu:8 #SBATCH --partition=hopper-prod # Adjust this for your cluster #SBATCH --output=/fsx/h4/logs/%x-%j.out # Adjust this for your cluster #SBATCH --err=/fsx/h4/logs/%x-%j.err # Adjust this for your cluster set -x -e source ~/.bashrc cond...
alignment-handbook/recipes/launch.slurm/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...
alignment-handbook/src/alignment/configs.py/0
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[workspace] members = [ "candle-core", "candle-datasets", "candle-examples", "candle-book", "candle-nn", "candle-pyo3", "candle-transformers", "candle-wasm-examples/*", "candle-wasm-tests", ] exclude = [ "candle-flash-attn", "candle-kernels", "candle-metal-kernels", "cand...
candle/Cargo.toml/0
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# Advanced Cuda usage
candle/candle-book/src/cuda/README.md/0
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# Serialization
candle/candle-book/src/training/serialization.md/0
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#![allow(dead_code)] use libc::{c_char, c_double, c_float, c_int, c_long, c_ulong}; mod ffi { use super::*; extern "C" { // It would be nice to be able to switch to the NEWLAPACK version of the function but this // seems to trigger some link error. Available function names can be seen here: ...
candle/candle-core/src/accelerate.rs/0
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//! Types for elements that can be stored and manipulated using tensors. #![allow(clippy::redundant_closure_call)] use crate::backend::BackendStorage; use crate::{CpuStorage, Error, Result}; /// The different types of elements allowed in tensors. #[derive(Debug, Copy, Clone, PartialEq, Eq, Hash)] pub enum DType { ...
candle/candle-core/src/dtype.rs/0
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use super::{GgmlDType, QStorage}; use crate::{DType, MetalDevice, MetalStorage, Result}; use metal::Buffer; use std::sync::Arc; pub struct QMetalStorage { dtype: GgmlDType, device: MetalDevice, buffer: Arc<Buffer>, } impl QMetalStorage { pub fn dtype(&self) -> GgmlDType { self.dtype } ...
candle/candle-core/src/quantized/metal.rs/0
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use anyhow::Result; use candle_core::{DType, Device::Cpu, Tensor}; #[test] fn display_scalar() -> Result<()> { let t = Tensor::new(1234u32, &Cpu)?; let s = format!("{t}"); assert_eq!(&s, "[1234]\nTensor[[], u32]"); let t = t.to_dtype(DType::F32)?.neg()?; let s = format!("{}", (&t / 10.0)?); ass...
candle/candle-core/tests/display_tests.rs/0
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pub mod tinystories;
candle/candle-datasets/src/nlp/mod.rs/0
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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
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use candle::backend::BackendStorage; use candle::{CpuStorage, CustomOp1, DType, Device, IndexOp, Layout, Result, Shape, Tensor, D}; use candle_nn::{Embedding, Linear, Module, RmsNorm}; use cudarc::nccl::safe::{Comm, ReduceOp}; use half::f16; use serde::Deserialize; use std::rc::Rc; use std::sync::{Arc, Mutex}; use sup...
candle/candle-examples/examples/llama_multiprocess/model.rs/0
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use crate::encodec_model; use candle::{DType, Device, Result, Tensor, D}; use candle_nn::{ embedding, layer_norm, linear_no_bias, Activation, Embedding, LayerNorm, Linear, Module, VarBuilder, }; use candle_transformers::models::t5; // https://github.com/huggingface/transformers/blob/cd4584e3c809bb9e1392ccd3fe3...
candle/candle-examples/examples/musicgen/musicgen_model.rs/0
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#![allow(unused)] #[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use candle::Result; use clap::{Parser, Subcommand}; mod gym_env; mod vec_gym_env; mod ddpg; mod policy_gradient; #[derive(Parser)] struct Args { #[command(subcommand)] command:...
candle/candle-examples/examples/reinforcement-learning/main.rs/0
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// https://github.com/openai/whisper/blob/main/whisper/model.py/rgs // TODO: // - Batch size greater than 1. // - More token filters (SuppressBlanks, ApplyTimestampRules). #[cfg(feature = "accelerate")] extern crate accelerate_src; #[cfg(feature = "mkl")] extern crate intel_mkl_src; use anyhow::{Error as E, Result};...
candle/candle-examples/examples/whisper/main.rs/0
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; mod model; use model::{Multiples, YoloV8, YoloV8Pose}; use candle::{DType, Device, IndexOp, Result, Tensor}; use candle_nn::{Module, VarBuilder}; use candle_transformers::object_detection::{non_maximum_sup...
candle/candle-examples/examples/yolo-v8/main.rs/0
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/****************************************************************************** * Copyright (c) 2023, Tri Dao. ******************************************************************************/ #pragma once #include "cute/algorithm/copy.hpp" #include "cutlass/cutlass.h" #include "cutlass/layout/layout.h" #include <cu...
candle/candle-flash-attn/kernels/kernel_traits.h/0
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#include "cuda_fp16.h" #include "cuda_bf16.h" // Table showing which features are supported on which compute capability // https://docs.nvidia.com/cuda/cuda-c-programming-guide/#features-and-technical-specifications // FIXME: the minimum compute capabilities are just guesses since the table is not specific enough #i...
candle/candle-kernels/src/compatibility.cuh/0
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use metal::{ Buffer, CommandBufferRef, CompileOptions, ComputeCommandEncoderRef, ComputePipelineState, Device, Function, FunctionConstantValues, Library, MTLDataType, MTLSize, NSUInteger, }; use std::collections::HashMap; use std::ffi::c_void; use std::sync::RwLock; const AFFINE: &str = include_str!("affine.me...
candle/candle-metal-kernels/src/lib.rs/0
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use candle::{Result, Tensor}; use serde::Deserialize; #[derive(Debug, Clone, Copy, PartialEq, Deserialize, Default)] #[serde(rename_all = "lowercase")] pub enum Activation { #[default] Gelu, #[serde(alias = "gelu_new")] NewGelu, Relu, Relu2, Relu6, Silu, Sigmoid, HardSigmoid, ...
candle/candle-nn/src/activation.rs/0
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//! A `VarBuilder` is used to retrieve variables used by a model. These variables can either come //! from a pre-trained checkpoint, e.g. using `VarBuilder::from_mmaped_safetensors`, or initialized //! for training, e.g. using `VarBuilder::from_varmap`. use crate::VarMap; use candle::{safetensors::Load, DType, Device, ...
candle/candle-nn/src/var_builder.rs/0
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#[cfg(feature = "mkl")] extern crate intel_mkl_src; #[cfg(feature = "accelerate")] extern crate accelerate_src; use candle::{Device, Result, Tensor}; use candle_onnx::onnx::{GraphProto, ModelProto, NodeProto, ValueInfoProto}; use std::collections::HashMap; const INPUT_X: &str = "x"; const INPUT_Y: &str = "y"; const ...
candle/candle-onnx/tests/ops.rs/0
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import math from typing import Any import candle from candle import Tensor from .module import Module # See https://github.com/pytorch/pytorch/blob/main/torch/nn/modules/linear.py class Identity(Module): r"""A placeholder identity operator that is argument-insensitive. Args: args: any argument (unu...
candle/candle-pyo3/py_src/candle/nn/linear.py/0
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# See: https://raw.githubusercontent.com/huggingface/tokenizers/main/bindings/python/stub.py import argparse import inspect import os from typing import Optional import black from pathlib import Path import re INDENT = " " * 4 GENERATED_COMMENT = "# Generated content DO NOT EDIT\n" TYPING = """from typing import Any,...
candle/candle-pyo3/stub.py/0
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use super::blip_text; use super::with_tracing::{conv2d, linear, Conv2d, Linear}; use candle::{Module, Result, Tensor, D}; use candle_nn::{layer_norm, Conv2dConfig, LayerNorm, VarBuilder}; use serde::Deserialize; #[derive(Debug, Clone, Deserialize)] pub struct VisionConfig { pub hidden_size: usize, pub intermed...
candle/candle-transformers/src/models/blip.rs/0
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pub mod bert; pub mod bigcode; pub mod blip; pub mod blip_text; pub mod convmixer; pub mod dinov2; pub mod distilbert; pub mod efficientnet; pub mod falcon; pub mod jina_bert; pub mod llama; pub mod llama2_c; pub mod llama2_c_weights; pub mod marian; pub mod mistral; pub mod mixformer; pub mod mixtral; pub mod mobileon...
candle/candle-transformers/src/models/mod.rs/0
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use candle::{IndexOp, Result, Tensor}; use candle_nn::{Module, VarBuilder}; use super::transformer::TwoWayTransformer; #[derive(Debug)] struct MlpMaskDecoder { layers: Vec<super::Linear>, sigmoid_output: bool, span: tracing::Span, } impl MlpMaskDecoder { fn new( input_dim: usize, hidd...
candle/candle-transformers/src/models/segment_anything/mask_decoder.rs/0
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//! 2D UNet Building Blocks //! use super::attention::{ AttentionBlock, AttentionBlockConfig, SpatialTransformer, SpatialTransformerConfig, }; use super::resnet::{ResnetBlock2D, ResnetBlock2DConfig}; use crate::models::with_tracing::{conv2d, Conv2d}; use candle::{Module, Result, Tensor, D}; use candle_nn as nn; #[...
candle/candle-transformers/src/models/stable_diffusion/unet_2d_blocks.rs/0
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use super::common::{AttnBlock, GlobalResponseNorm, LayerNormNoWeights, TimestepBlock, WLayerNorm}; use candle::{DType, Module, Result, Tensor, D}; use candle_nn::VarBuilder; #[derive(Debug)] pub struct ResBlockStageB { depthwise: candle_nn::Conv2d, norm: WLayerNorm, channelwise_lin1: candle_nn::Linear, ...
candle/candle-transformers/src/models/wuerstchen/diffnext.rs/0
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<html> <head> <meta content="text/html;charset=utf-8" http-equiv="Content-Type" /> <title>Candle Bert</title> </head> <body></body> </html> <!DOCTYPE html> <html> <head> <meta charset="UTF-8" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" /> <style> @import u...
candle/candle-wasm-examples/bert/lib-example.html/0
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<html> <head> <meta content="text/html;charset=utf-8" http-equiv="Content-Type" /> <title>Candle Llama.c Rust/WASM</title> </head> <body></body> </html> <!DOCTYPE html> <html> <head> <meta charset="UTF-8" /> <meta name="viewport" content="width=device-width, initial-scale=1.0" /> <style> ...
candle/candle-wasm-examples/llama2-c/lib-example.html/0
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[package] name = "candle-wasm-example-sam" version.workspace = true edition.workspace = true description.workspace = true repository.workspace = true keywords.workspace = true categories.workspace = true license.workspace = true [dependencies] candle = { workspace = true } candle-nn = { workspace = true } candle-trans...
candle/candle-wasm-examples/segment-anything/Cargo.toml/0
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export async function extractEmbeddings( worker, weightsURL, tokenizerURL, configURL, modelID, sentences, updateStatus, normalize_embeddings = true ) { return new Promise((resolve, reject) => { worker.postMessage({ weightsURL, tokenizerURL, configURL, modelID, sentenc...
candle/candle-wasm-examples/t5/utils.js/0
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[package] name = "candle-wasm-example-yolo" version.workspace = true edition.workspace = true description.workspace = true repository.workspace = true keywords.workspace = true categories.workspace = true license.workspace = true [dependencies] candle = { workspace = true } candle-nn = { workspace = true } num-traits ...
candle/candle-wasm-examples/yolo/Cargo.toml/0
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pub fn add(left: usize, right: usize) -> usize { left + right } #[cfg(test)] mod tests { use super::*; #[test] fn it_works() { let result = add(2, 2); assert_eq!(result, 4); } }
candle/candle-wasm-tests/src/lib.rs/0
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# Prompt templates These are the templates used to format the conversation history for different models used in HuggingChat. Set them in your `.env.local` [like so](https://github.com/huggingface/chat-ui#chatprompttemplate). ## Llama 2 ```env <s>[INST] <<SYS>>\n{{preprompt}}\n<</SYS>>\n\n{{#each messages}}{{#ifUser}...
chat-ui/PROMPTS.md/0
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<script lang="ts"> import type { readAndCompressImage } from "browser-image-resizer"; import type { Model } from "$lib/types/Model"; import type { Assistant } from "$lib/types/Assistant"; import { onMount } from "svelte"; import { applyAction, enhance } from "$app/forms"; import { base } from "$app/paths"; impo...
chat-ui/src/lib/components/AssistantSettings.svelte/0
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<script lang="ts"> export let checked: boolean; export let name: string; </script> <input bind:checked type="checkbox" {name} class="peer pointer-events-none absolute opacity-0" /> <div aria-checked={checked} aria-roledescription="switch" aria-label="switch" role="switch" tabindex="0" class="relative inline-fl...
chat-ui/src/lib/components/Switch.svelte/0
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<script lang="ts"> export let classNames = ""; </script> <svg class={classNames} xmlns="http://www.w3.org/2000/svg" aria-hidden="true" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 20 20" > ><path fill-rule="evenodd" d="M1.5 10a8.5 8.5 0 1 0 17 0a...
chat-ui/src/lib/components/icons/IconInternet.svelte/0
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import { buildPrompt } from "$lib/buildPrompt"; import type { TextGenerationStreamOutput } from "@huggingface/inference"; import type { Endpoint } from "../endpoints"; import { z } from "zod"; export const endpointOllamaParametersSchema = z.object({ weight: z.number().int().positive().default(1), model: z.any(), ty...
chat-ui/src/lib/server/endpoints/ollama/endpointOllama.ts/0
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import { base } from "$app/paths"; import { ERROR_MESSAGES, error } from "$lib/stores/errors"; import { share } from "./utils/share"; import { page } from "$app/stores"; import { get } from "svelte/store"; import { getShareUrl } from "./utils/getShareUrl"; export async function shareConversation(id: string, title: stri...
chat-ui/src/lib/shareConversation.ts/0
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import type { ObjectId } from "mongodb"; import type { User } from "./User"; import type { Assistant } from "./Assistant"; import type { Timestamps } from "./Timestamps"; export interface Report extends Timestamps { _id: ObjectId; createdBy: User["_id"] | string; assistantId: Assistant["_id"]; }
chat-ui/src/lib/types/Report.ts/0
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import type { Conversation } from "$lib/types/Conversation"; import { sha256 } from "./sha256"; export async function hashConv(conv: Conversation) { // messages contains the conversation message but only the immutable part const messages = conv.messages.map((message) => { return (({ from, id, content, webSearchId ...
chat-ui/src/lib/utils/hashConv.ts/0
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import { collections } from "$lib/server/database"; import { authCondition } from "$lib/server/auth"; import { z } from "zod"; import { ObjectId } from "mongodb"; export async function GET({ locals, params }) { const id = z.string().parse(params.id); const convId = new ObjectId(id); if (locals.user?._id || locals....
chat-ui/src/routes/api/conversation/[id]/+server.ts/0
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import { authCondition } from "$lib/server/auth"; import { collections } from "$lib/server/database"; import { error } from "@sveltejs/kit"; import { ObjectId } from "mongodb"; import { z } from "zod"; import type { RequestHandler } from "./$types"; import { downloadFile } from "$lib/server/files/downloadFile"; export...
chat-ui/src/routes/conversation/[id]/output/[sha256]/+server.ts/0
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import { base } from "$app/paths"; import { redirect } from "@sveltejs/kit"; export async function load({ parent, params }) { const data = await parent(); const model = data.models.find(({ id }) => id === params.model); if (!model || model.unlisted) { throw redirect(302, `${base}/settings`); } return data; }...
chat-ui/src/routes/settings/[...model]/+page.ts/0
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# Process audio data This guide shows specific methods for processing audio datasets. Learn how to: - Resample the sampling rate. - Use [`~Dataset.map`] with audio datasets. For a guide on how to process any type of dataset, take a look at the <a class="underline decoration-sky-400 decoration-2 font-semibold" href="...
datasets/docs/source/audio_process.mdx/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 applicable law or agreed...
datasets/docs/source/quickstart.mdx/0
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # 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....
datasets/metrics/accuracy/accuracy.py/0
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# Metric Card for Competition MATH ## Metric description This metric is used to assess performance on the [Mathematics Aptitude Test of Heuristics (MATH) dataset](https://huggingface.co/datasets/competition_math). It first canonicalizes the inputs (e.g., converting `1/2` to `\\frac{1}{2}`) and then computes accurac...
datasets/metrics/competition_math/README.md/0
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# Copyright 2020 The HuggingFace Datasets Authors. # # 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 ...
datasets/metrics/google_bleu/google_bleu.py/0
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# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor. # # 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....
datasets/metrics/mse/mse.py/0
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# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # 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....
datasets/metrics/sari/sari.py/0
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# Metric Card for WER ## Metric description Word error rate (WER) is a common metric of the performance of an automatic speech recognition (ASR) system. The general difficulty of measuring the performance of ASR systems lies in the fact that the recognized word sequence can have a different length from the reference...
datasets/metrics/wer/README.md/0
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# Copyright 2020 The TensorFlow Datasets Authors. # # 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...
datasets/src/datasets/download/mock_download_manager.py/0
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# Copyright 2020 The HuggingFace Authors. # # 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 to...
datasets/src/datasets/formatting/tf_formatter.py/0
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# Copyright 2020 The HuggingFace Datasets Authors # # 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...
datasets/src/datasets/metric.py/0
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from typing import List import datasets from datasets.tasks import ImageClassification from ..folder_based_builder import folder_based_builder logger = datasets.utils.logging.get_logger(__name__) class ImageFolderConfig(folder_based_builder.FolderBasedBuilderConfig): """BuilderConfig for ImageFolder.""" ...
datasets/src/datasets/packaged_modules/imagefolder/imagefolder.py/0
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from .parallel import parallel_backend, parallel_map, ParallelBackendConfig # noqa F401
datasets/src/datasets/parallel/__init__.py/0
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