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Gemma finetuning bugfixes (#86)
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models/Gemma/README.md

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@@ -31,13 +31,13 @@ You can download either model from the NVIDIA NGC Catalog, using the NGC CLI. Th
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To download the model, execute one of the following commands, based on which model you want to use:
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```bash
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ngc registry model download-version "nvidia/nemo/gemma_2b_base:1.0"
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ngc registry model download-version "nvidia/nemo/gemma_2b_base:1.1"
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```
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or
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```bash
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ngc registry model download-version "nvidia/nemo/gemma_7b_base:1.0"
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ngc registry model download-version "nvidia/nemo/gemma_7b_base:1.1"
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```
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## Getting NeMo Framework

models/Gemma/lora.ipynb

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"To download the model, execute one of the following commands, based on which model you want to use:\n",
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"\n",
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"```bash\n",
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"ngc registry model download-version \"nvidia/nemo/gemma_2b_base:1.0\"\n",
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"ngc registry model download-version \"nvidia/nemo/gemma_2b_base:1.1\"\n",
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"```\n",
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"\n",
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"or\n",
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"\n",
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"```bash\n",
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"ngc registry model download-version \"nvidia/nemo/gemma_7b_base:1.0\"\n",
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"ngc registry model download-version \"nvidia/nemo/gemma_7b_base:1.1\"\n",
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"```"
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]
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},
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" },\n",
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" \"test_ds\": {\n",
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" \"file_names\": [\"pubmedqa_test.jsonl\"],\n",
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" \"names\": [\"pubmedqa\"]\n",
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" \"names\": [\"pubmedqa\"],\n",
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" \"add_bos\": True\n",
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" }\n",
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"}, merge=True)"
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]

models/Gemma/sft.ipynb

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"To download the model, execute one of the following commands, based on which model you want to use:\n",
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"\n",
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"```bash\n",
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"ngc registry model download-version \"nvidia/nemo/gemma_2b_base:1.0\"\n",
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"ngc registry model download-version \"nvidia/nemo/gemma_2b_base:1.1\"\n",
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"```\n",
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"\n",
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"or\n",
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"\n",
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"```bash\n",
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"ngc registry model download-version \"nvidia/nemo/gemma_7b_base:1.0\"\n",
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"ngc registry model download-version \"nvidia/nemo/gemma_7b_base:1.1\"\n",
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"```"
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]
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},
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" model.data.train_ds.micro_batch_size=1 \\\n",
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" model.data.train_ds.global_batch_size=128 \\\n",
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" model.data.train_ds.file_path=../databricks-dolly-15k-output.jsonl \\\n",
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" model.data.train_ds.add_bos=True \\\n",
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" model.data.validation_ds.micro_batch_size=1 \\\n",
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" model.data.validation_ds.global_batch_size=128 \\\n",
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" model.data.validation_ds.drop_last=True \\\n",

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