lnit

Author: philschmid

site/en/gemma/docs/core/huggingface_text_finetune_qlora.ipynb

@@ -319,7 +319,7 @@
         "id": "3a062e371c81"
       },
       "source": [
-        "The `SFTTrainer` supports a native integration with `peft`, which makes it straightforward to efficiently tune LLMs using QLoRA. You only need to create a `LoraConfig` and provide it to the trainer."
+        "The `SFTTrainer` supports a built-in integration with `peft`, which makes it straightforward to efficiently tune LLMs using QLoRA. You only need to create a `LoraConfig` and provide it to the trainer."
       ]
     },
     {
@@ -385,7 +385,7 @@
         "    push_to_hub=True,                       # push model to hub\n",
         "    report_to=\"tensorboard\",                # report metrics to tensorboard\n",
         "    dataset_kwargs={\n",
-        "        \"add_special_tokens\": False, # We template with special tokens\n",
+        "        \"add_special_tokens\": False, # Template with special tokens\n",
         "        \"append_concat_token\": True, # Add EOS token as separator token between examples\n",
         "    }\n",
         ")"