Create DataParallel model if several GPUs #1
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bearpelican
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Jan 7, 2019
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.
qwang70
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Mar 2, 2019
Create DataParallel model if several GPUs
qwang70
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Mar 2, 2019
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.
thomwolf
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Apr 23, 2019
Pulling commits from main repo
thomwolf
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Jun 22, 2019
Correct a broken link and its context.
thomwolf
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Sep 10, 2019
changes in return statement of evaluate function
thomwolf
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Sep 18, 2019
roberta, xlnet for multiple choice
Closed
thomwolf
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Oct 22, 2019
This was referenced Nov 30, 2019
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stevezheng23
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Mar 24, 2020
Merge changes from huggingface/transformers to stevezheng23/transformers
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patrickvonplaten
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Jun 7, 2020
…utput_attentions fix pytorch tests
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KobeKnowles
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Jun 8, 2022
gante
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Jun 28, 2022
* fix: code structure in few cases. * fix: code structure to align tf models. * fix: layer naming, bn layer still remains. * chore: change default epsilon and momentum in bn.
gante
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Jun 29, 2022
* chore: initial commit Copied the torch implementation of regnets and porting the code to tf step by step. Also introduced an output layer which was needed for regnets. * chore: porting the rest of the modules to tensorflow did not change the documentation yet, yet to try the playground on the model * Fix initilizations (#1) * fix: code structure in few cases. * fix: code structure to align tf models. * fix: layer naming, bn layer still remains. * chore: change default epsilon and momentum in bn. * chore: styling nits. * fix: cross-loading bn params. * fix: regnet tf model, integration passing. * add: tests for TF regnet. * fix: code quality related issues. * chore: added rest of the files. * minor additions.. * fix: repo consistency. * fix: regnet tf tests. * chore: reorganize dummy_tf_objects for regnet. * chore: remove checkpoint var. * chore: remov unnecessary files. * chore: run make style. * Update docs/source/en/model_doc/regnet.mdx Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * chore: PR feedback I. * fix: pt test. thanks to @ydshieh. * New adaptive pooler (#3) * feat: new adaptive pooler Co-authored-by: @Rocketknight1 * chore: remove image_size argument. Co-authored-by: matt <rocketknight1@gmail.com> Co-authored-by: matt <rocketknight1@gmail.com> * Empty-Commit * chore: remove image_size comment. * chore: remove playground_tf.py * chore: minor changes related to spacing. * chore: make style. * Update src/transformers/models/regnet/modeling_tf_regnet.py Co-authored-by: amyeroberts <aeroberts4444@gmail.com> * Update src/transformers/models/regnet/modeling_tf_regnet.py Co-authored-by: amyeroberts <aeroberts4444@gmail.com> * chore: refactored __init__. * chore: copied from -> taken from./g * adaptive pool -> global avg pool, channel check. * chore: move channel check to stem. * pr comments - minor refactor and add regnets to doc tests. * Update src/transformers/models/regnet/modeling_tf_regnet.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * minor fix in the xlayer. * Empty-Commit * chore: removed from_pt=True. Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: matt <rocketknight1@gmail.com> Co-authored-by: amyeroberts <aeroberts4444@gmail.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Muennighoff
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Jul 9, 2022
Lintang/noncausal attention
viclzhu
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Jul 18, 2022
* chore: initial commit Copied the torch implementation of regnets and porting the code to tf step by step. Also introduced an output layer which was needed for regnets. * chore: porting the rest of the modules to tensorflow did not change the documentation yet, yet to try the playground on the model * Fix initilizations (huggingface#1) * fix: code structure in few cases. * fix: code structure to align tf models. * fix: layer naming, bn layer still remains. * chore: change default epsilon and momentum in bn. * chore: styling nits. * fix: cross-loading bn params. * fix: regnet tf model, integration passing. * add: tests for TF regnet. * fix: code quality related issues. * chore: added rest of the files. * minor additions.. * fix: repo consistency. * fix: regnet tf tests. * chore: reorganize dummy_tf_objects for regnet. * chore: remove checkpoint var. * chore: remov unnecessary files. * chore: run make style. * Update docs/source/en/model_doc/regnet.mdx Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> * chore: PR feedback I. * fix: pt test. thanks to @ydshieh. * New adaptive pooler (huggingface#3) * feat: new adaptive pooler Co-authored-by: @Rocketknight1 * chore: remove image_size argument. Co-authored-by: matt <rocketknight1@gmail.com> Co-authored-by: matt <rocketknight1@gmail.com> * Empty-Commit * chore: remove image_size comment. * chore: remove playground_tf.py * chore: minor changes related to spacing. * chore: make style. * Update src/transformers/models/regnet/modeling_tf_regnet.py Co-authored-by: amyeroberts <aeroberts4444@gmail.com> * Update src/transformers/models/regnet/modeling_tf_regnet.py Co-authored-by: amyeroberts <aeroberts4444@gmail.com> * chore: refactored __init__. * chore: copied from -> taken from./g * adaptive pool -> global avg pool, channel check. * chore: move channel check to stem. * pr comments - minor refactor and add regnets to doc tests. * Update src/transformers/models/regnet/modeling_tf_regnet.py Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com> * minor fix in the xlayer. * Empty-Commit * chore: removed from_pt=True. Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com> Co-authored-by: matt <rocketknight1@gmail.com> Co-authored-by: amyeroberts <aeroberts4444@gmail.com> Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
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hannan72
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Sep 4, 2023
update flax_utils.py
ocavue
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Sep 13, 2023
Add pipelines!
ydshieh
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Dec 7, 2023
* 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>
ydshieh
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Dec 8, 2023
* 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>
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LysandreJik
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Mar 15, 2024
* 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>
LysandreJik
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Apr 10, 2024
Cohere Model Release
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DaryaTereshchenko
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Dec 17, 2024
Add new model
SunMarc
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Jan 15, 2025
* 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>
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