Create DataParallel model if several GPUs #1

VictorSanh · 2018-11-03T14:10:20Z

No description provided.

Adds an example for loading a pre-trained BERT model and fine tune it as a language model (masked tokens & nextSentence) on your target corpus.

Create DataParallel model if several GPUs

Adds an example for loading a pre-trained BERT model and fine tune it as a language model (masked tokens & nextSentence) on your target corpus.

Pulling commits from main repo

Correct a broken link and its context.

Update torchscript.rst

changes in return statement of evaluate function

merege from original repo

roberta, xlnet for multiple choice

update

Merge changes from huggingface/transformers to stevezheng23/transformers

…utput_attentions fix pytorch tests

update flax_utils.py

Add pipelines!

* Draft version of new KV Caching This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks) / StreamingLLM (https://arxiv.org/abs/2309.17453) to be easily implemented in a third-party or in transformers directly * Address numerous PR suggestions 1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic. 2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls. 3. Remove __bool__ and __getitem__ magic as they're confusing. 4. past_key_values.update(key, value, idx) now returns key, value. 5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR. 6. Separate key_cache and value_cache. Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method. * Integrate (Sink)Cache with Llama FA2 * Move from/to_legacy_cache to ...Model class * Undo unnecessary newline change * Match import style * working generate * Add tests; Simplify code; Apply changes to Mistral and Persimmon * fix rebase mess * a few more manual fixes * last manual fix * propagate changes to phi * upgrade test * add use_legacy_cache docstring; beef up tests * reintroduce unwanted deletes --------- Co-authored-by: Tom Aarsen <Cubiegamedev@gmail.com>

* Draft version of new KV Caching This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks) / StreamingLLM (https://arxiv.org/abs/2309.17453) to be easily implemented in a third-party or in transformers directly * Address numerous PR suggestions 1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic. 2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls. 3. Remove __bool__ and __getitem__ magic as they're confusing. 4. past_key_values.update(key, value, idx) now returns key, value. 5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR. 6. Separate key_cache and value_cache. Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method. * Implement the SinkCache through backward+forward rotations * Integrate (Sink)Cache with Llama FA2 * Set use_legacy_cache=True as default, allows for test passes * Move from/to_legacy_cache to ...Model class * Undo unnecessary newline change * Remove copy utility from deprecated OpenLlama * Match import style * manual rebase with main * Cache class working with generate (#1) * Draft version of new KV Caching This should allow Attention Sinks (https://github.com/tomaarsen/attention_sinks) / StreamingLLM (https://arxiv.org/abs/2309.17453) to be easily implemented in a third-party or in transformers directly * Address numerous PR suggestions 1. Move layer_idx from cache to ...Attention. Removes confusing set_layer_idx magic. 2. Always convert past_key_values to Cache instance at the start of ...Attention, removes all other isinstance calls. 3. Remove __bool__ and __getitem__ magic as they're confusing. 4. past_key_values.update(key, value, idx) now returns key, value. 5. Add use_legacy_cache flag, defaults to None, i.e. Falsey. This breaks generate for now, until 1) the cache is used is generate() or 2) use_legacy_cache is defaulted to True in generate() until we change it in another PR. 6. Separate key_cache and value_cache. Some work is still needed to see if the SinkCache can conveniently be implemented with just one update method. * Integrate (Sink)Cache with Llama FA2 * Move from/to_legacy_cache to ...Model class * Undo unnecessary newline change * Match import style * working generate * Add tests; Simplify code; Apply changes to Mistral and Persimmon * fix rebase mess * a few more manual fixes * last manual fix * propagate changes to phi * upgrade test * add use_legacy_cache docstring; beef up tests * reintroduce unwanted deletes --------- Co-authored-by: Tom Aarsen <Cubiegamedev@gmail.com> * move import * add default to model_kwargs.get('use_legacy_cache') * correct failing test * Apply suggestions from code review Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> * apply PR suggestions * fix failing test * Apply suggestions from code review Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: Tom Aarsen <37621491+tomaarsen@users.noreply.github.com> * PR comments * tmp commit * add docstrings * more tests, more docstrings, add to docs * derp * tmp commit * tmp dbg * more dbg * fix beam search bug * cache can be a list of tuples in some models * fix group beam search * all but sinkcache integration tests * fix sink cache and add hard integration test * now also compatible with input_embeds input * PR comments * add Cache support to Phi+FA2 * make fixup --------- Co-authored-by: Joao Gante <joao@huggingface.co> Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com> Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Cohere Model Release (#1) Cohere Model Release * Remove unnecessary files and code (#2) Some cleanup * Delete cohere-model directory (#3) * Make Fix (#5) * Pr fixes (#6) * fixes for pr * pr fixes for the format * pr fixes for the format * src/transformers/models/auto/tokenization_auto.py * Tokenizer test (#8) * tokenizer test * format fix * Adding Docs and other minor changes (#7) * Add modeling tests (#9) * Smol Fix (#11) * tokenization tests are fixed * format fixes * fix pr doc tests * fix pr doc tests * fix pr doc tests * fix pr style check * small changes in cohere.md * FIX: Address final comments for transformers integration (#13) * fix modeling final nits and add proper test file * for now leave empty tests * add integration test * push new test * fix modeling cohere (#14) * Update chat templates to use the new API (#15) --------- Co-authored-by: ahmetustun <ahmetustun89@gmail.com> Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

Cohere Model Release

Add new model

* gptqmodel Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update readme Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * 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 <zx@modelcloud.ai> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> * Revert quantizer_gptq.py (#2) * revert quantizer_gptq.py change * pass **kwargs * limit gptqmodel and optimum version Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix warning Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix version check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * revert unrelated changes Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * enable gptqmodel tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix requires gptq Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * 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 <lrl@lbx.dev> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format again Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update gptqmodel version (#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 (#7) * fix format and tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix memory check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix device mismatch Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix result check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * update tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * review: update docs (#10) * review: update docs (#12) * review: update docs * fix typo * update tests for gptqmodel Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update document (#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 <qubitium@modelcloud.ai> * 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 <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/overview.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/overview.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> --------- Signed-off-by: jiqing-feng <jiqing.feng@intel.com> Co-authored-by: LRL-ModelCloud <165116337+LRL-ModelCloud@users.noreply.github.com> Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> Co-authored-by: ZX-ModelCloud <165115237+ZX-ModelCloud@users.noreply.github.com> Co-authored-by: LRL <lrl@lbx.dev> Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com> Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* gptqmodel Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update readme Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * gptqmodel need use checkpoint_format (huggingface#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 <zx@modelcloud.ai> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> * Revert quantizer_gptq.py (huggingface#2) * revert quantizer_gptq.py change * pass **kwargs * limit gptqmodel and optimum version Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix warning Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix version check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * revert unrelated changes Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * enable gptqmodel tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix requires gptq Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * Fix Transformer compat (huggingface#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 <lrl@lbx.dev> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format again Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update gptqmodel version (huggingface#6) * update gptqmodel version * update gptqmodel version * fix unit test (huggingface#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 <jiqing.feng@intel.com> * fix memory check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix device mismatch Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix result check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * update tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * review: update docs (huggingface#10) * review: update docs (huggingface#12) * review: update docs * fix typo * update tests for gptqmodel Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * 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 <qubitium@modelcloud.ai> * 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 <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/overview.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/overview.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> --------- Signed-off-by: jiqing-feng <jiqing.feng@intel.com> Co-authored-by: LRL-ModelCloud <165116337+LRL-ModelCloud@users.noreply.github.com> Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> Co-authored-by: ZX-ModelCloud <165115237+ZX-ModelCloud@users.noreply.github.com> Co-authored-by: LRL <lrl@lbx.dev> Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com> Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>

* 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 <59462357+stevhliu@users.noreply.github.com> * Update spqr.md * Enable gptqmodel (#35012) * gptqmodel Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update readme Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * 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 <zx@modelcloud.ai> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> * Revert quantizer_gptq.py (#2) * revert quantizer_gptq.py change * pass **kwargs * limit gptqmodel and optimum version Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix warning Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix version check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * revert unrelated changes Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * enable gptqmodel tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix requires gptq Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * 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 <lrl@lbx.dev> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> * fix format Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix format again Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update gptqmodel version (#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 (#7) * fix format and tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix memory check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix device mismatch Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix result check Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * Update src/transformers/quantizers/quantizer_gptq.py Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> * update tests Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * review: update docs (#10) * review: update docs (#12) * review: update docs * fix typo * update tests for gptqmodel Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * update document (#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 <qubitium@modelcloud.ai> * 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 <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/gptq.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/overview.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Update docs/source/en/quantization/overview.md Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> --------- Signed-off-by: jiqing-feng <jiqing.feng@intel.com> Co-authored-by: LRL-ModelCloud <165116337+LRL-ModelCloud@users.noreply.github.com> Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> Co-authored-by: ZX-ModelCloud <165115237+ZX-ModelCloud@users.noreply.github.com> Co-authored-by: LRL <lrl@lbx.dev> Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com> Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> * Fix : Nemotron Processor in GGUF conversion (#35708) * fixing nemotron processor * make style * Update docs/source/en/quantization/spqr.md Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com> * Add missing TOC to doc --------- Signed-off-by: jiqing-feng <jiqing.feng@intel.com> Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com> Co-authored-by: jiqing-feng <jiqing.feng@intel.com> Co-authored-by: LRL-ModelCloud <165116337+LRL-ModelCloud@users.noreply.github.com> Co-authored-by: ZX-ModelCloud <zx@modelcloud.ai> Co-authored-by: Qubitium-ModelCloud <qubitium@modelcloud.ai> Co-authored-by: ZX-ModelCloud <165115237+ZX-ModelCloud@users.noreply.github.com> Co-authored-by: LRL <lrl@lbx.dev> Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com> Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com> Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

…CollatorIntegrationTest::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 huggingface#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`.

…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`.

Create DataParallel model if several GPUs

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VictorSanh merged commit a6efe12 into master Nov 3, 2018

thomwolf deleted the multi-gpu-support branch November 4, 2018 00:35

davidkim205 mentioned this pull request Jan 4, 2019

BertTokenizer에서 do_lower_case에 관계없이 #162

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qwang70 pushed a commit to DRL36/pytorch-pretrained-BERT that referenced this pull request Mar 2, 2019

Merge pull request huggingface#1 from huggingface/multi-gpu-support

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Create DataParallel model if several GPUs

thomwolf pushed a commit that referenced this pull request Apr 23, 2019

Merge pull request #1 from huggingface/master

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Pulling commits from main repo

maeotaku mentioned this pull request May 23, 2019

bert->onnx ->caffe2 weird error #633

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thomwolf pushed a commit that referenced this pull request Jun 22, 2019

Merge pull request #1 from papower1/papower1-patch-1

ada0d8f

Correct a broken link and its context.

thomwolf pushed a commit that referenced this pull request Jul 25, 2019

Merge pull request #1 from sukuya/sukuya-patch-1

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Update torchscript.rst

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Merge pull request #1 from SKRohit/SKRohit-patch-1

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changes in return statement of evaluate function

thomwolf pushed a commit that referenced this pull request Sep 11, 2019

Merge pull request #1 from huggingface/master

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merege from original repo

thomwolf pushed a commit that referenced this pull request Sep 18, 2019

Merge pull request #1 from erenup/run_multiple_choice

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roberta, xlnet for multiple choice

HongyanJiao mentioned this pull request Sep 19, 2019

traced_model #1291

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fabrahman mentioned this pull request Oct 9, 2019

How is it possible to furthur tune gpt-2(or gpt) in a seq2seq manner? #1464

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thomwolf pushed a commit that referenced this pull request Oct 22, 2019

Merge pull request #1 from huggingface/master

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update

TheEdoardo93 mentioned this pull request Nov 4, 2019

GPT2 text generation repeat #1725

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devroy73 mentioned this pull request Nov 10, 2019

Multi GPU dataparallel crash #1779

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snaik2016 mentioned this pull request Nov 21, 2019

Distilling GPT2 with gives OOM #1897

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This was referenced Nov 30, 2019

Can we use tf.keras.mixed_precision.experimental.set_policy ? #2004

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tf.keras.mixed_precision.experimental.Policy #2005

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gradient-school mentioned this pull request Dec 2, 2019

[ALBERT] : ValueError: Layer #1 (named "predictions") expects 11 weight(s), but the saved weights have 10 element(s). #2024

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Aidanlochbihler mentioned this pull request Feb 21, 2020

RuntimeError: Expected tensor for argument #1 'indices' to have scalar type Long; but got torch.cuda.IntTensor instead (while checking arguments for embedding) #2952

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volker42maru mentioned this pull request Mar 18, 2020

TF BERT not FP16 compatible? #3320

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stevezheng23 added a commit to stevezheng23/transformers that referenced this pull request Mar 24, 2020

Merge pull request huggingface#1 from huggingface/master

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Merge changes from huggingface/transformers to stevezheng23/transformers

go-dustin mentioned this pull request May 4, 2020

Pytorch T5 does not run on GPU #2472

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yyHaker mentioned this pull request May 12, 2020

why squad.py did not reproduce squad1.1 report result? #4301

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dbaxter240 mentioned this pull request May 18, 2020

Issues with the EncoderDecoderModel for sequence to sequence tasks #4443

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patrickvonplaten added a commit to patrickvonplaten/transformers that referenced this pull request Jun 7, 2020

Merge pull request huggingface#1 from patrickvonplaten/fix_tests_in_o…

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…utput_attentions fix pytorch tests

lwmlyy mentioned this pull request Aug 15, 2023

add util for ram efficient loading of model when using fsdp #25107

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hannan72 pushed a commit to hannan72/transformers that referenced this pull request Sep 4, 2023

Merge pull request huggingface#1 from ondewo/hannan_updates_flax

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update flax_utils.py

ocavue pushed a commit to ocavue/transformers that referenced this pull request Sep 13, 2023

Merge pull request huggingface#1 from xenova/pipelines

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Add pipelines!

daehuikim mentioned this pull request Dec 10, 2023

[Question] What is the main difference between "AutoModelForCasualLM" and "PeftModelForCausalLM"? #27928

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changyeli mentioned this pull request Jan 14, 2024

Possible data converting problem when using flash attention 2 with whisper #27260

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oObelix mentioned this pull request Mar 7, 2024

model_config = model.config.to_dict() - AttributeError: 'dict' object has no attribute 'to_dict' huggingface/setfit#498

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LysandreJik referenced this pull request in LysandreJik/transformers Apr 10, 2024

Cohere Model Release (#1)

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Cohere Model Release

guangy10 mentioned this pull request Jul 29, 2024

Export to ExecuTorch #32253

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jjbuck mentioned this pull request Nov 11, 2024

Changes required to save_model for certain models (e.g., Phi 3.5 Vision) #34690

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HichTala mentioned this pull request Dec 6, 2024

[Clean-up] Planned removal of the max_size argument #35090

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DaryaTereshchenko referenced this pull request in DaryaTereshchenko/transformers Dec 17, 2024

Merge pull request #1 from DaryaTereshchenko/new_branch_name

eafd847

Add new model

leonardtang mentioned this pull request Mar 1, 2025

GRPO Reward Weight Scheduler #36490

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Rocketknight1 mentioned this pull request Mar 6, 2025

add-long-vita #36553

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leonardtang mentioned this pull request Mar 9, 2025

GRPO Reward Weight Scheduler huggingface/trl#3036

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SilverSoldier mentioned this pull request Apr 2, 2025

torch.compile graph break when tuning llama with FA2 #37199

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kreil mentioned this pull request May 14, 2025

eval_loss not found when training a peft model using trainer.py / losses not retrieved from base model where appropriate #38130

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