From 0fe03afeb82e1a435a75704d1f434c47e49a0bbb Mon Sep 17 00:00:00 2001 From: Maxime Grenu <69890511+cluster2600@users.noreply.github.com> Date: Wed, 23 Jul 2025 14:43:11 +0200 Subject: [PATCH] Fix typos and grammar issues in documentation and code (#39598) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - Fix Cyrillic 'Р' to Latin 'P' in Portuguese language link (README.md) - Fix 'meanginful' to 'meaningful' in training documentation - Fix duplicate 'Cohere' reference in modular transformers documentation - Fix duplicate 'the the' in trainer and chat command comments 🤖 Generated with [Claude Code](https://claude.ai/code) Co-authored-by: Claude Co-authored-by: Claude --- README.md | 2 +- docs/source/en/modular_transformers.md | 2 +- docs/source/en/training.md | 2 +- src/transformers/commands/chat.py | 2 +- src/transformers/trainer.py | 2 +- 5 files changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index 13afb112ca..7e909a66f3 100644 --- a/README.md +++ b/README.md @@ -44,7 +44,7 @@ limitations under the License. 日本語 | हिन्दी | Русский | - Рortuguês | + Português | తెలుగు | Français | Deutsch | diff --git a/docs/source/en/modular_transformers.md b/docs/source/en/modular_transformers.md index 76d77e2ffd..d97de838af 100644 --- a/docs/source/en/modular_transformers.md +++ b/docs/source/en/modular_transformers.md @@ -94,7 +94,7 @@ ValueError: You defined `RobertaEmbeddings` in the modular_roberta.py, it should ## Implementing a modular file -The easiest way to start is by browsing Transformers for a model similar to yours in order to inherit from it. Some good starting points are [Mistral](./model_doc/mistral), [Qwen2](./model_doc/qwen2), [Cohere](./model_doc/cohere) and [Cohere](./model_doc/cohere2), and [Llama](./model_doc/llama). Refer to the table below for components your model might be using and where you can inherit from. +The easiest way to start is by browsing Transformers for a model similar to yours in order to inherit from it. Some good starting points are [Mistral](./model_doc/mistral), [Qwen2](./model_doc/qwen2), [Cohere](./model_doc/cohere) and [Cohere2](./model_doc/cohere2), and [Llama](./model_doc/llama). Refer to the table below for components your model might be using and where you can inherit from. | Component | Model | |---|---| diff --git a/docs/source/en/training.md b/docs/source/en/training.md index 7f2a622b48..c859229383 100644 --- a/docs/source/en/training.md +++ b/docs/source/en/training.md @@ -74,7 +74,7 @@ model = AutoModelForSequenceClassification.from_pretrained("google-bert/bert-bas ``` > [!TIP] -> The message above is a reminder that the models pretrained head is discarded and replaced with a randomly initialized classification head. The randomly initialized head needs to be fine-tuned on your specific task to output meanginful predictions. +> The message above is a reminder that the models pretrained head is discarded and replaced with a randomly initialized classification head. The randomly initialized head needs to be fine-tuned on your specific task to output meaningful predictions. With the model loaded, set up your training hyperparameters in [`TrainingArguments`]. Hyperparameters are variables that control the training process - such as the learning rate, batch size, number of epochs - which in turn impacts model performance. Selecting the correct hyperparameters is important and you should experiment with them to find the best configuration for your task. diff --git a/src/transformers/commands/chat.py b/src/transformers/commands/chat.py index 81a01932a0..378e932d94 100644 --- a/src/transformers/commands/chat.py +++ b/src/transformers/commands/chat.py @@ -426,7 +426,7 @@ class ChatCommand(BaseTransformersCLICommand): # 2. c. [no processing needed] lists are lists of ints because `generate` doesn't take lists of strings :) # We also mention in the help message that we only accept lists of ints for now. - # 3. Join the the result into a comma separated string + # 3. Join the result into a comma separated string generate_flags_string = ", ".join([f"{k}: {v}" for k, v in generate_flags_as_dict.items()]) # 4. Add the opening/closing brackets diff --git a/src/transformers/trainer.py b/src/transformers/trainer.py index 6dc2a11436..380ccbf406 100755 --- a/src/transformers/trainer.py +++ b/src/transformers/trainer.py @@ -529,7 +529,7 @@ class Trainer: kernel_config = self.args.liger_kernel_config if self.args.liger_kernel_config is not None else {} if isinstance(model, PreTrainedModel): - # Patch the model with liger kernels. Use the the specified or default kernel configurations. + # Patch the model with liger kernels. Use the specified or default kernel configurations. _apply_liger_kernel_to_instance(model=model, **kernel_config) elif hasattr(model, "get_base_model") and isinstance(model.get_base_model(), PreTrainedModel): # Patch the base model with liger kernels where model is a PeftModel. Use the specified or default kernel configurations.