Update docs-text-classification-python-multi-label-go_emotions.ipynb (#2107)

mgoin · web-flow · commit b4d4d6132df5 · 2024-02-22T15:57:45.000-05:00
* Update docs-text-classification-python-multi-label-go_emotions.ipynb

* Update docs-text-classification-python-multi-label-go_emotions.ipynb
diff --git a/integrations/huggingface-transformers/tutorials/text-classification/docs-text-classification-python-multi-label-go_emotions.ipynb b/integrations/huggingface-transformers/tutorials/text-classification/docs-text-classification-python-multi-label-go_emotions.ipynb
@@ -649,7 +649,7 @@
    },
    "outputs": [],
    "source": [
-    "%cat ./transfer_recipe/recipe/recipe_original.md"
+    "%cat ./transfer_recipe/recipe.md"
    ]
   },
   {
@@ -811,13 +811,11 @@
     "model_kwargs = {\"config\": config}\n",
     "model_kwargs[\"state_dict\"], s_delayed = SparseAutoModel._loadable_state_dict(model_path)\n",
     "model = AutoModelForSequenceClassification.from_pretrained(model_path, **model_kwargs,)\n",
-    "SparseAutoModel.log_model_load(model, model_path, \"student\", s_delayed)     # prints metrics on sparsity profile\n",
     "\n",
     "# initialize teacher using familiar HF AutoModel\n",
     "teacher_kwargs = {\"config\": teacher_config}\n",
     "teacher_kwargs[\"state_dict\"], t_delayed = SparseAutoModel._loadable_state_dict(teacher_path)\n",
     "teacher = AutoModelForSequenceClassification.from_pretrained(teacher_path, **teacher_kwargs,)\n",
-    "SparseAutoModel.log_model_load(teacher, teacher_path, \"teacher\", t_delayed) # prints metrics on sparsity profile"
    ]
   },
   {

Original file line number	Diff line number	Diff line change
`@@ -649,7 +649,7 @@`
`649`	`649`	`},`
`650`	`650`	`"outputs": [],`
`651`	`651`	`"source": [`
`652`		`- "%cat ./transfer_recipe/recipe/recipe_original.md"`
	`652`	`+ "%cat ./transfer_recipe/recipe.md"`
`653`	`653`	`]`
`654`	`654`	`},`
`655`	`655`	`{`
`@@ -811,13 +811,11 @@`
`811`	`811`	`"model_kwargs = {\"config\": config}\n",`
`812`	`812`	`"model_kwargs[\"state_dict\"], s_delayed = SparseAutoModel._loadable_state_dict(model_path)\n",`
`813`	`813`	`"model = AutoModelForSequenceClassification.from_pretrained(model_path, **model_kwargs,)\n",`
`814`		`- "SparseAutoModel.log_model_load(model, model_path, \"student\", s_delayed) # prints metrics on sparsity profile\n",`
`815`	`814`	`"\n",`
`816`	`815`	`"# initialize teacher using familiar HF AutoModel\n",`
`817`	`816`	`"teacher_kwargs = {\"config\": teacher_config}\n",`
`818`	`817`	`"teacher_kwargs[\"state_dict\"], t_delayed = SparseAutoModel._loadable_state_dict(teacher_path)\n",`
`819`	`818`	`"teacher = AutoModelForSequenceClassification.from_pretrained(teacher_path, **teacher_kwargs,)\n",`
`820`		`- "SparseAutoModel.log_model_load(teacher, teacher_path, \"teacher\", t_delayed) # prints metrics on sparsity profile"`
`821`	`819`	`]`
`822`	`820`	`},`
`823`	`821`	`{`