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stas00
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Oct 22, 2020
* neFLOs calculation, logging, and reloading (#1) * testing distributed consecutive batches * fixed AttributeError from DataParallel * removed verbosity * rotate with use_mtime=True * removed print * fixed interaction with gradient accumulation * indent formatting * distributed neflo counting * fixed typo * fixed typo * mean distributed losses * exporting log history * moved a few functions * floating_point_ops clarification for transformers with parameter-reuse * code quality * double import * made flo estimation more task-agnostic * only logging flos if computed * code quality * unused import * Update src/transformers/trainer.py Co-authored-by: Sylvain Gugger <[email protected]> * Update src/transformers/modeling_utils.py Co-authored-by: Sylvain Gugger <[email protected]> * Sylvain review * Update src/transformers/modeling_utils.py Co-authored-by: Sylvain Gugger <[email protected]> * black Co-authored-by: Sylvain Gugger <[email protected]>
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Oct 22, 2020
* ready for PR * cleanup * correct FSMT_PRETRAINED_MODEL_ARCHIVE_LIST * fix * perfectionism * revert change from another PR * odd, already committed this one * non-interactive upload workaround * backup the failed experiment * store langs in config * workaround for localizing model path * doc clean up as in huggingface#6956 * style * back out debug mode * document: run_eval.py --num_beams 10 * remove unneeded constant * typo * re-use bart's Attention * re-use EncoderLayer, DecoderLayer from bart * refactor * send to cuda and fp16 * cleanup * revert (moved to another PR) * better error message * document run_eval --num_beams * solve the problem of tokenizer finding the right files when model is local * polish, remove hardcoded config * add a note that the file is autogenerated to avoid losing changes * prep for org change, remove unneeded code * switch to model4.pt, update scores * s/python/bash/ * missing init (but doesn't impact the finetuned model) * cleanup * major refactor (reuse-bart) * new model, new expected weights * cleanup * cleanup * full link * fix model type * merge porting notes * style * cleanup * have to create a DecoderConfig object to handle vocab_size properly * doc fix * add note (not a public class) * parametrize * - add bleu scores integration tests * skip test if sacrebleu is not installed * cache heavy models/tokenizers * some tweaks * remove tokens that aren't used * more purging * simplify code * switch to using decoder_start_token_id * add doc * Revert "major refactor (reuse-bart)" This reverts commit 226dad1. * decouple from bart * remove unused code #1 * remove unused code #2 * remove unused code #3 * update instructions * clean up * move bleu eval to examples * check import only once * move data+gen script into files * reuse via import * take less space * add prepare_seq2seq_batch (auto-tested) * cleanup * recode test to use json instead of yaml * ignore keys not needed * use the new -y in transformers-cli upload -y * [xlm tok] config dict: fix str into int to match definition (huggingface#7034) * [s2s] --eval_max_generate_length (huggingface#7018) * Fix CI with change of name of nlp (huggingface#7054) * nlp -> datasets * More nlp -> datasets * Woopsie * More nlp -> datasets * One last * extending to support allen_nlp wmt models - allow a specific checkpoint file to be passed - more arg settings - scripts for allen_nlp models * sync with changes * s/fsmt-wmt/wmt/ in model names * s/fsmt-wmt/wmt/ in model names (p2) * s/fsmt-wmt/wmt/ in model names (p3) * switch to a better checkpoint * typo * make non-optional args such - adjust tests where possible or skip when there is no other choice * consistency * style * adjust header * cards moved (model rename) * use best custom hparams * update info * remove old cards * cleanup * s/stas/facebook/ * update scores * s/allen_nlp/allenai/ * url maps aren't needed * typo * move all the doc / build /eval generators to their own scripts * cleanup * Apply suggestions from code review Co-authored-by: Lysandre Debut <[email protected]> * Apply suggestions from code review Co-authored-by: Lysandre Debut <[email protected]> * fix indent * duplicated line * style * use the correct add_start_docstrings * oops * resizing can't be done with the core approach, due to 2 dicts * check that the arg is a list * style * style Co-authored-by: Sam Shleifer <[email protected]> Co-authored-by: Sylvain Gugger <[email protected]> Co-authored-by: Lysandre Debut <[email protected]>
stas00
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Dec 11, 2020
There is a tiny typo in the code "transformers/examples/language-modeling/run_mlm_wwm.py" at line 284. [Details.](huggingface#9012)
stas00
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Feb 9, 2022
…5416) * added classes to get started with constrained beam search * in progress, think i can directly force tokens now but not yet with the round robin * think now i have total control, now need to code the bank selection * technically works as desired, need to optimize and fix design choices leading to undersirable outputs * complete PR #1 without disjunctive decoding * removed incorrect tests * Delete k.txt * Delete test.py * Delete test.sh * revert changes to test scripts * genutils * full implementation with testing, no disjunctive yet * shifted docs * passing all tests realistically ran locally * removing accidentally included print statements * fixed source of error in initial PR test * fixing the get_device() vs device trap * fixed documentation docstrings about constrained_beam_search * fixed tests having failing for Speech2TextModel's floating point inputs * fix cuda long tensor * added examples and testing for them and founx & fixed a bug in beam_search and constrained_beam_search * deleted accidentally added test halting code with assert False * code reformat * Update tests/test_generation_utils.py Co-authored-by: Patrick von Platen <[email protected]> * Update tests/test_generation_utils.py Co-authored-by: Patrick von Platen <[email protected]> * Update tests/test_generation_utils.py Co-authored-by: Patrick von Platen <[email protected]> * Update tests/test_generation_utils.py Co-authored-by: Patrick von Platen <[email protected]> * Update tests/test_generation_utils.py * fixing based on comments on PR * took out the testing code that should but work fails without the beam search moditification ; style changes * fixing comments issues * docstrings for ConstraintListState * typo in PhrsalConstraint docstring * docstrings improvements Co-authored-by: Patrick von Platen <[email protected]>
stas00
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Mar 12, 2022
) * added classes to get started with constrained beam search * in progress, think i can directly force tokens now but not yet with the round robin * think now i have total control, now need to code the bank selection * technically works as desired, need to optimize and fix design choices leading to undersirable outputs * complete PR #1 without disjunctive decoding * removed incorrect tests * Delete k.txt * Delete test.py * Delete test.sh * revert changes to test scripts * genutils * full implementation with testing, no disjunctive yet * shifted docs * passing all tests realistically ran locally * removing accidentally included print statements * fixed source of error in initial PR test * fixing the get_device() vs device trap * fixed documentation docstrings about constrained_beam_search * fixed tests having failing for Speech2TextModel's floating point inputs * fix cuda long tensor * added examples and testing for them and founx & fixed a bug in beam_search and constrained_beam_search * deleted accidentally added test halting code with assert False * code reformat * Update tests/test_generation_utils.py Co-authored-by: Patrick von Platen <[email protected]> * Update tests/test_generation_utils.py Co-authored-by: Patrick von Platen <[email protected]> * Update tests/test_generation_utils.py Co-authored-by: Patrick von Platen <[email protected]> * Update tests/test_generation_utils.py Co-authored-by: Patrick von Platen <[email protected]> * Update tests/test_generation_utils.py * fixing based on comments on PR * took out the testing code that should but work fails without the beam search moditification ; style changes * fixing comments issues * docstrings for ConstraintListState * typo in PhrsalConstraint docstring * docstrings improvements * finished adding what is sort of an opinionated implementation of disjunctive generation, but it revealed errors in inner beam search logic during testing. * fixed bug found in constrained beam search that used beam_idx that were not global across all the batches * disjunctive constraint working 100% correctly * passing all tests * Accidentally included mlruns * Update src/transformers/generation_beam_constraints.py Co-authored-by: Patrick von Platen <[email protected]> * Update src/transformers/generation_beam_constraints.py Co-authored-by: Patrick von Platen <[email protected]> * complete overhaul of type complexities and other nits * strict type checks in generate() * fixing second round of feedback by narsil * fixed failing generation test because of type check overhaul * generation test fail fix * fixing test fails Co-authored-by: Patrick von Platen <[email protected]>
stas00
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Mar 7, 2025
* Resolve vptq conflict * Rename spqr package to spqr_quant * Get rid of aqlm mention * Start working on tests * Resolve ruff code checks * Ruff format * Isort * Test updates * Add gpu tag * Rename to modules_to_not_convert * Config update * Docs and config update * Docs and config update * Update to update_torch_dtype * spqr config parameter validation * Ruff update * Apply ruff fixes * Test fixes * Ruff update * Mark tests as @slow again; Ruff; Docstring update * Ruff * Remove absolute path * Resolve typo * Remove redundandt log * Check accelerate/spqr availability * Ruff fix * Check if the config contains proper shapes * Ruff test * Documentation update * overview update * Ruff checks * Ruff code quality * Make style * Update docs/source/en/quantization/spqr.md Co-authored-by: Steven Liu <[email protected]> * Update spqr.md * Enable gptqmodel (huggingface#35012) * gptqmodel Signed-off-by: jiqing-feng <[email protected]> * fix format Signed-off-by: jiqing-feng <[email protected]> * update readme Signed-off-by: jiqing-feng <[email protected]> * gptqmodel need use checkpoint_format (#1) * gptqmodel need use checkpoint_format * fix quantize * Update quantization_config.py * Update quantization_config.py * Update quantization_config.py --------- Co-authored-by: ZX-ModelCloud <[email protected]> Co-authored-by: Qubitium-ModelCloud <[email protected]> * Revert quantizer_gptq.py (#2) * revert quantizer_gptq.py change * pass **kwargs * limit gptqmodel and optimum version Signed-off-by: jiqing-feng <[email protected]> * fix format Signed-off-by: jiqing-feng <[email protected]> * fix warning Signed-off-by: jiqing-feng <[email protected]> * fix version check Signed-off-by: jiqing-feng <[email protected]> * revert unrelated changes Signed-off-by: jiqing-feng <[email protected]> * enable gptqmodel tests Signed-off-by: jiqing-feng <[email protected]> * fix requires gptq Signed-off-by: jiqing-feng <[email protected]> * Fix Transformer compat (#3) * revert quantizer_gptq.py change * pass **kwargs * add meta info * cleanup * cleanup * Update quantization_config.py * hf_select_quant_linear pass checkpoint_format and meta * fix GPTQTestCUDA * Update test_gptq.py * gptqmodel.hf_select_quant_linear() now does not select ExllamaV2 * cleanup * add backend * cleanup * cleanup * no need check exllama version * Update quantization_config.py * lower checkpoint_format and backend * check none * cleanup * Update quantization_config.py * fix self.use_exllama == False * spell * fix unittest * fix unittest --------- Co-authored-by: LRL <[email protected]> Co-authored-by: Qubitium-ModelCloud <[email protected]> * fix format Signed-off-by: jiqing-feng <[email protected]> * fix format again Signed-off-by: jiqing-feng <[email protected]> * update gptqmodel version (huggingface#6) * update gptqmodel version * update gptqmodel version * fix unit test (#5) * update gptqmodel version * update gptqmodel version * "not self.use_exllama" is not equivalent to "self.use_exllama==False" * fix unittest * update gptqmodel version * backend is loading_attibutes (huggingface#7) * fix format and tests Signed-off-by: jiqing-feng <[email protected]> * fix memory check Signed-off-by: jiqing-feng <[email protected]> * fix device mismatch Signed-off-by: jiqing-feng <[email protected]> * fix result check Signed-off-by: jiqing-feng <[email protected]> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <[email protected]> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <[email protected]> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <[email protected]> * update tests Signed-off-by: jiqing-feng <[email protected]> * review: update docs (huggingface#10) * review: update docs (huggingface#12) * review: update docs * fix typo * update tests for gptqmodel Signed-off-by: jiqing-feng <[email protected]> * update document (huggingface#9) * update overview.md * cleanup * Update overview.md * Update overview.md * Update overview.md * update gptq.md * Update gptq.md * Update gptq.md * Update gptq.md * Update gptq.md * Update gptq.md * Update gptq.md --------- Co-authored-by: Qubitium-ModelCloud <[email protected]> * typo * doc note for asymmetric quant * typo with apple silicon(e) * typo for marlin * column name revert: review * doc rocm support * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/quantization/overview.md Co-authored-by: Steven Liu <[email protected]> * Update docs/source/en/quantization/overview.md Co-authored-by: Steven Liu <[email protected]> --------- Signed-off-by: jiqing-feng <[email protected]> Co-authored-by: LRL-ModelCloud <[email protected]> Co-authored-by: ZX-ModelCloud <[email protected]> Co-authored-by: Qubitium-ModelCloud <[email protected]> Co-authored-by: ZX-ModelCloud <[email protected]> Co-authored-by: LRL <[email protected]> Co-authored-by: Marc Sun <[email protected]> Co-authored-by: Mohamed Mekkouri <[email protected]> Co-authored-by: Steven Liu <[email protected]> * Fix : Nemotron Processor in GGUF conversion (huggingface#35708) * fixing nemotron processor * make style * Update docs/source/en/quantization/spqr.md Co-authored-by: Arthur <[email protected]> * Add missing TOC to doc --------- Signed-off-by: jiqing-feng <[email protected]> Co-authored-by: Steven Liu <[email protected]> Co-authored-by: jiqing-feng <[email protected]> Co-authored-by: LRL-ModelCloud <[email protected]> Co-authored-by: ZX-ModelCloud <[email protected]> Co-authored-by: Qubitium-ModelCloud <[email protected]> Co-authored-by: ZX-ModelCloud <[email protected]> Co-authored-by: LRL <[email protected]> Co-authored-by: Marc Sun <[email protected]> Co-authored-by: Mohamed Mekkouri <[email protected]> Co-authored-by: Arthur <[email protected]>
stas00
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Mar 7, 2025
…uggingface#36457) Fixed 2 issues regarding `tests/trainer/test_data_collator.py::TFDataCollatorIntegrationTest::test_all_mask_replacement`: 1. I got the error `RuntimeError: "bernoulli_tensor_cpu_p_" not implemented for 'Long'`. This is because the `mask_replacement_prob=1` and `torch.bernoulli` doesn't accept this type (which would be a `torch.long` dtype instead. I fixed this by manually casting the probability arguments in the `__post_init__` function of `DataCollatorForLanguageModeling`. 2. I also got the error `tensorflow.python.framework.errors_impl.InvalidArgumentError: cannot compute Equal as input #1(zero-based) was expected to be a int64 tensor but is a int32 tensor [Op:Equal]` due to the line `tf.reduce_all((batch["input_ids"] == inputs) | (batch["input_ids"] == tokenizer.mask_token_id))` in `test_data_collator.py`. This occurs because the type of the `inputs` variable is `tf.int32`. Solved this by manually casting it to `tf.int64` in the test, as the expected return type of `batch["input_ids"]` is `tf.int64`.
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Trying huggingface#7887