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[urls to hub] Replace outdated model tags with their now-canonical pipeline types (#14617)

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* Replace outdated model tags with their now-canonical pipeline types

* spam the CI till it's green
This commit is contained in:
Julien Chaumond
2021-12-06 10:35:01 +01:00
committed by GitHub
parent c824d7ed48
commit 6cdc3a7844
15 changed files with 16 additions and 15 deletions
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2
examples/flax/language-modeling/run_clm_flax.py
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@@ -17,7 +17,7 @@
Pre-training/Fine-tuning the library models for causal language modeling (GPT, GPT-2, CTRL, ...) on a text file or a dataset. Pre-training/Fine-tuning the library models for causal language modeling (GPT, GPT-2, CTRL, ...) on a text file or a dataset.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=causal-lm https://huggingface.co/models?filter=text-generation
""" """
# You can also adapt this script on your own causal language modeling task. Pointers for this are left as comments. # You can also adapt this script on your own causal language modeling task. Pointers for this are left as comments.

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examples/flax/language-modeling/run_mlm_flax.py
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@@ -18,7 +18,7 @@ Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBER
text file or a dataset. text file or a dataset.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=masked-lm https://huggingface.co/models?filter=fill-mask
""" """
import json import json
import logging import logging

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examples/pytorch/language-modeling/run_clm.py
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@@ -17,7 +17,7 @@
Fine-tuning the library models for causal language modeling (GPT, GPT-2, CTRL, ...) on a text file or a dataset. Fine-tuning the library models for causal language modeling (GPT, GPT-2, CTRL, ...) on a text file or a dataset.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=causal-lm https://huggingface.co/models?filter=text-generation
""" """
# You can also adapt this script on your own causal language modeling task. Pointers for this are left as comments. # You can also adapt this script on your own causal language modeling task. Pointers for this are left as comments.

2
examples/pytorch/language-modeling/run_clm_no_trainer.py
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@@ -18,7 +18,7 @@ Fine-tuning the library models for causal language modeling (GPT, GPT-2, CTRL, .
on a text file or a dataset without using HuggingFace Trainer. on a text file or a dataset without using HuggingFace Trainer.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=causal-lm https://huggingface.co/models?filter=text-generation
""" """
# You can also adapt this script on your own causal language modeling task. Pointers for this are left as comments. # You can also adapt this script on your own causal language modeling task. Pointers for this are left as comments.

2
examples/pytorch/language-modeling/run_mlm.py
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@@ -17,7 +17,7 @@
Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBERTa...) on a text file or a dataset. Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBERTa...) on a text file or a dataset.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=masked-lm https://huggingface.co/models?filter=fill-mask
""" """
# You can also adapt this script on your own masked language modeling task. Pointers for this are left as comments. # You can also adapt this script on your own masked language modeling task. Pointers for this are left as comments.

2
examples/pytorch/language-modeling/run_mlm_no_trainer.py
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@@ -18,7 +18,7 @@ Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBER
on a text file or a dataset without using HuggingFace Trainer. on a text file or a dataset without using HuggingFace Trainer.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=masked-lm https://huggingface.co/models?filter=fill-mask
""" """
# You can also adapt this script on your own mlm task. Pointers for this are left as comments. # You can also adapt this script on your own mlm task. Pointers for this are left as comments.

2
examples/research_projects/jax-projects/dataset-streaming/run_mlm_flax_stream.py
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@@ -18,7 +18,7 @@ Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBER
text file or a dataset. text file or a dataset.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=masked-lm https://huggingface.co/models?filter=fill-mask
""" """
import logging import logging
import os import os

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examples/research_projects/jax-projects/hybrid_clip/run_hybrid_clip.py
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@@ -20,7 +20,7 @@ The script can be used to train CLIP like models for languages other than englis
a text encoder pre-trained in the desired language. Currently this script support the following vision a text encoder pre-trained in the desired language. Currently this script support the following vision
and text models: and text models:
Vision models: ViT(https://huggingface.co/models?filter=vit), CLIP (https://huggingface.co/models?filter=clip) Vision models: ViT(https://huggingface.co/models?filter=vit), CLIP (https://huggingface.co/models?filter=clip)
Text models: BERT, ROBERTa (https://huggingface.co/models?filter=masked-lm) Text models: BERT, ROBERTa (https://huggingface.co/models?filter=fill-mask)
""" """
import json import json

2
examples/research_projects/mlm_wwm/run_mlm_wwm.py
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@@ -17,7 +17,7 @@ Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBER
text file or a dataset. text file or a dataset.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=masked-lm https://huggingface.co/models?filter=fill-mask
""" """
# You can also adapt this script on your own masked language modeling task. Pointers for this are left as comments. # You can also adapt this script on your own masked language modeling task. Pointers for this are left as comments.

2
examples/research_projects/performer/run_mlm_performer.py
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@@ -17,7 +17,7 @@ Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBER
text file or a dataset. text file or a dataset.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=masked-lm https://huggingface.co/models?filter=fill-mask
""" """
import logging import logging
import os import os

2
examples/tensorflow/language-modeling/run_clm.py
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@@ -18,7 +18,7 @@ Fine-tuning the library models for causal language modeling (GPT-2, GPT-Neo...)
on a text file or a dataset without using HuggingFace Trainer. on a text file or a dataset without using HuggingFace Trainer.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=causal-lm https://huggingface.co/models?filter=text-generation
""" """
# You can also adapt this script on your own clm task. Pointers for this are left as comments. # You can also adapt this script on your own clm task. Pointers for this are left as comments.

2
examples/tensorflow/language-modeling/run_mlm.py
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@@ -18,7 +18,7 @@ Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBER
on a text file or a dataset without using HuggingFace Trainer. on a text file or a dataset without using HuggingFace Trainer.
Here is the full list of checkpoints on the hub that can be fine-tuned by this script: Here is the full list of checkpoints on the hub that can be fine-tuned by this script:
https://huggingface.co/models?filter=masked-lm https://huggingface.co/models?filter=fill-mask
""" """
# You can also adapt this script on your own mlm task. Pointers for this are left as comments. # You can also adapt this script on your own mlm task. Pointers for this are left as comments.

2
src/transformers/pipelines/fill_mask.py
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@@ -40,7 +40,7 @@ class FillMaskPipeline(Pipeline):
The models that this pipeline can use are models that have been trained with a masked language modeling objective, The models that this pipeline can use are models that have been trained with a masked language modeling objective,
which includes the bi-directional models in the library. See the up-to-date list of available models on which includes the bi-directional models in the library. See the up-to-date list of available models on
`huggingface.co/models <https://huggingface.co/models?filter=masked-lm>`__. `huggingface.co/models <https://huggingface.co/models?filter=fill-mask>`__.
.. note:: .. note::

3
src/transformers/pipelines/text2text_generation.py
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@@ -31,7 +31,8 @@ class Text2TextGenerationPipeline(Pipeline):
following task identifier: :obj:`"text2text-generation"`. following task identifier: :obj:`"text2text-generation"`.
The models that this pipeline can use are models that have been fine-tuned on a translation task. See the The models that this pipeline can use are models that have been fine-tuned on a translation task. See the
up-to-date list of available models on `huggingface.co/models <https://huggingface.co/models?filter=seq2seq>`__. up-to-date list of available models on `huggingface.co/models
<https://huggingface.co/models?filter=text2text-generation>`__.
Usage:: Usage::

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src/transformers/pipelines/text_generation.py
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@@ -23,7 +23,7 @@ class TextGenerationPipeline(Pipeline):
The models that this pipeline can use are models that have been trained with an autoregressive language modeling The models that this pipeline can use are models that have been trained with an autoregressive language modeling
objective, which includes the uni-directional models in the library (e.g. gpt2). See the list of available models objective, which includes the uni-directional models in the library (e.g. gpt2). See the list of available models
on `huggingface.co/models <https://huggingface.co/models?filter=causal-lm>`__. on `huggingface.co/models <https://huggingface.co/models?filter=text-generation>`__.
""" """
# Prefix text to help Transformer-XL and XLNet with short prompts as proposed by Aman Rusia # Prefix text to help Transformer-XL and XLNet with short prompts as proposed by Aman Rusia