[urls to hub] Replace outdated model tags with their now-canonical pipeline types (#14617)

* Replace outdated model tags with their now-canonical pipeline types

* spam the CI till it's green

examples/flax/language-modeling/run_clm_flax.py

@@ -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.
 
 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.
 

examples/flax/language-modeling/run_mlm_flax.py

@@ -18,7 +18,7 @@ Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBER
 text file or a dataset.
 
 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 logging

examples/pytorch/language-modeling/run_clm.py

@@ -17,7 +17,7 @@
 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:
-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.
 

examples/pytorch/language-modeling/run_clm_no_trainer.py

@@ -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.
 
 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.
 

examples/pytorch/language-modeling/run_mlm.py

@@ -17,7 +17,7 @@
 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:
-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.
 

examples/pytorch/language-modeling/run_mlm_no_trainer.py

@@ -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.
 
 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.
 

examples/research_projects/jax-projects/dataset-streaming/run_mlm_flax_stream.py

@@ -18,7 +18,7 @@ Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBER
 text file or a dataset.
 
 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 os

examples/research_projects/jax-projects/hybrid_clip/run_hybrid_clip.py

@@ -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
 and text models:
 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

examples/research_projects/mlm_wwm/run_mlm_wwm.py

@@ -17,7 +17,7 @@ Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBER
 text file or a dataset.
 
 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.
 

examples/research_projects/performer/run_mlm_performer.py

@@ -17,7 +17,7 @@ Fine-tuning the library models for masked language modeling (BERT, ALBERT, RoBER
 text file or a dataset.
 
 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 os

examples/tensorflow/language-modeling/run_clm.py

@@ -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.
 
 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.
 

examples/tensorflow/language-modeling/run_mlm.py

@@ -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.
 
 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.
 

src/transformers/pipelines/fill_mask.py

@@ -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,
     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::
 

src/transformers/pipelines/text2text_generation.py

@@ -31,7 +31,8 @@ class Text2TextGenerationPipeline(Pipeline):
     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
-    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::
 

src/transformers/pipelines/text_generation.py

@@ -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
     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