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Fix transformers examples #174

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merged 3 commits into from
Apr 25, 2024
Merged

Fix transformers examples #174

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3d355e4
Fix transformers example
Lothiraldan Apr 25, 2024
3e5e1d0
Switch to a maintained HF model
Lothiraldan Apr 25, 2024
6a82c97
Pin transformers to a slightly older version for now
Lothiraldan Apr 25, 2024
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2 changes: 1 addition & 1 deletion guides/get-started/Comet_Quickstart.ipynb
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Expand Up @@ -426,7 +426,7 @@
},
"outputs": [],
"source": [
"%pip install -U comet_ml torch datasets transformers scikit-learn accelerate"
"%pip install -U comet_ml torch datasets \"transformers<4.40.0\" scikit-learn accelerate"
]
},
{
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2 changes: 1 addition & 1 deletion integrations/llm/finetuning/alpaca-lora/notebooks/Alpaca_Lora_Finetuning_with_Comet.ipynb
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Expand Up @@ -88,7 +88,7 @@
"metadata": {},
"outputs": [],
"source": [
"%pip install -r alpaca-lora/requirements.txt scipy"
"%pip install -r alpaca-lora/requirements.txt scipy \"transformers<4.40.0\""
]
},
{
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36 changes: 18 additions & 18 deletions integrations/model-evaluation/gradio/notebooks/Gradio_and_Comet.ipynb
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Expand Up @@ -55,7 +55,7 @@
},
"outputs": [],
"source": [
"%pip install -U comet_ml gradio altair torch torchvision transformers requests Pillow"
"%pip install -U comet_ml gradio altair torch torchvision \"transformers<4.40.0\" requests Pillow"
]
},
{
Expand Down Expand Up @@ -118,7 +118,9 @@
"from PIL import Image\n",
"from torchvision import transforms\n",
"\n",
"torch.hub.download_url_to_file(\"https://github.com/pytorch/hub/raw/master/images/dog.jpg\", \"dog.jpg\")\n",
"torch.hub.download_url_to_file(\n",
" \"https://github.com/pytorch/hub/raw/master/images/dog.jpg\", \"dog.jpg\"\n",
")\n",
"\n",
"model = torch.hub.load(\"pytorch/vision:v0.6.0\", \"resnet18\", pretrained=True).eval()\n",
"\n",
Expand All @@ -138,9 +140,7 @@
"inputs = gr.Image()\n",
"outputs = gr.Label(num_top_classes=3)\n",
"\n",
"io = gr.Interface(\n",
" fn=predict, inputs=inputs, outputs=outputs, examples=[\"dog.jpg\"]\n",
")\n",
"io = gr.Interface(fn=predict, inputs=inputs, outputs=outputs, examples=[\"dog.jpg\"])\n",
"io.launch(inline=False, share=True)\n",
"\n",
"experiment = comet_ml.Experiment()\n",
Expand Down Expand Up @@ -200,7 +200,7 @@
" \"max_length\": 50,\n",
" \"temperature\": 0.7,\n",
" \"top_k\": 50,\n",
" \"no_repeat_ngram_size\": 2\n",
" \"no_repeat_ngram_size\": 2,\n",
"}\n",
"model = model.to(device)\n",
"tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)\n",
Expand All @@ -220,17 +220,14 @@
" )\n",
" return \".\".join(output.split(\".\")[:-1]) + \".\"\n",
"\n",
"\n",
"input_text = gr.Textbox(label=\"Input Prompt\")\n",
"output_text = gr.Textbox(label=\"Generated Output\")\n",
"io = gr.Interface(\n",
" generate_text,\n",
" inputs=input_text,\n",
" outputs=output_text,\n",
" examples=[\n",
" [\n",
" \"The dectective looked at the room full of suspects and said, \"\n",
" ]\n",
" ],\n",
" examples=[[\"The dectective looked at the room full of suspects and said, \"]],\n",
")\n",
"io.launch(inline=False, share=True)\n",
"\n",
Expand Down Expand Up @@ -273,9 +270,7 @@
"do_lower_case = True\n",
"model_version = \"distilbert-base-uncased-distilled-squad\"\n",
"\n",
"tokenizer = AutoTokenizer.from_pretrained(\n",
" model_version, do_lower_case=do_lower_case\n",
")\n",
"tokenizer = AutoTokenizer.from_pretrained(model_version, do_lower_case=do_lower_case)\n",
"tokenizer.pad_token = \"[PAD]\"\n",
"model = AutoModelForQuestionAnswering.from_pretrained(\n",
" model_version, output_attentions=True, pad_token_id=tokenizer.eos_token_id\n",
Expand All @@ -286,23 +281,28 @@
"\n",
"def qa_func(context, question):\n",
" prediction = qa(question=question, context=context)\n",
" answer = prediction['answer']\n",
" answer = prediction[\"answer\"]\n",
"\n",
" return answer\n",
"\n",
"\n",
"io = gr.Interface(\n",
" qa_func,\n",
" inputs=[\n",
" gr.Textbox(lines=7, label=\"Context\"),\n",
" gr.Textbox(label=\"Question\"),\n",
" ],\n",
" outputs=[gr.Textbox(label=\"Answer\")],\n",
" examples=[[\"\"\"A Moon landing is the arrival of a spacecraft on the surface of the Moon.\n",
" examples=[\n",
" [\n",
" \"\"\"A Moon landing is the arrival of a spacecraft on the surface of the Moon.\n",
" This includes both crewed and robotic missions. The first human-made object to touch the Moon was the Soviet Union's Luna 2, on 13 September 1959.\n",
" The United States' Apollo 11 was the first crewed mission to land on the Moon, on 20 July 1969. \n",
" There were six crewed U.S. landings between 1969 and 1972, and numerous uncrewed landings, with no soft landings happening between 22 August 1976 and 14 December 2013.\n",
" \"\"\", \"What year did the first crewed mission land on the moon?\"]\n",
" ]\n",
" \"\"\",\n",
" \"What year did the first crewed mission land on the moon?\",\n",
" ]\n",
" ],\n",
")\n",
"io.launch(inline=False, share=True)\n",
"\n",
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2 changes: 1 addition & 1 deletion ...ns/model-evaluation/gradio/notebooks/Logging_Model_Inferences_with_Comet_and_Gradio.ipynb
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Expand Up @@ -42,7 +42,7 @@
},
"outputs": [],
"source": [
"%pip install comet_ml torch transformers \"gradio>=4.0\" shap"
"%pip install comet_ml torch \"transformers<4.40.0\" \"gradio>=4.0\" shap"
]
},
{
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28 changes: 13 additions & 15 deletions integrations/model-training/hugging_face/notebooks/Comet_with_Hugging_Face_Trainer.ipynb
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Expand Up @@ -11,11 +11,13 @@
},
{
"cell_type": "markdown",
"metadata": {},
"metadata": {
"id": "5L-2VqFDWgGx"
},
"source": [
"[Hugging Face](https://huggingface.co/docs) is a community and data science platform that provides tools that enable users to build, train and deploy ML models based on open source (OS) code and technologies. Primarily known for their `transformers` library, Hugging Face has helped democratized access to these models by providing a unified API to train and evaluate a number of popular models for NLP. \n",
"[Hugging Face](https://huggingface.co/docs) is a community and data science platform that provides tools that enable users to build, train and deploy ML models based on open source (OS) code and technologies. Primarily known for their `transformers` library, Hugging Face has helped democratized access to these models by providing a unified API to train and evaluate a number of popular models for NLP.\n",
"\n",
"Comet integrates with Hugging Face's `Trainer` object, allowing you to log your model parameters, metrics, and assets such as model checkpoints. Learn more about our integration [here](https://www.comet.com/docs/v2/integrations/ml-frameworks/huggingface/) \n",
"Comet integrates with Hugging Face's `Trainer` object, allowing you to log your model parameters, metrics, and assets such as model checkpoints. Learn more about our integration [here](https://www.comet.com/docs/v2/integrations/ml-frameworks/huggingface/)\n",
"\n",
"Curious about how Comet can help you build better models, faster? Find out more about [Comet](https://www.comet.com/site/products/ml-experiment-tracking/?utm_campaign=transformers&utm_medium=colab) and our [other integrations](https://www.comet.ml/docs/v2/integrations/overview/)\n",
"\n",
Expand Down Expand Up @@ -82,7 +84,7 @@
},
"outputs": [],
"source": [
"PRE_TRAINED_MODEL_NAME = \"distilbert-base-uncased\"\n",
"PRE_TRAINED_MODEL_NAME = \"distilbert/distilroberta-base\"\n",
"SEED = 42"
]
},
Expand Down Expand Up @@ -138,7 +140,11 @@
"outputs": [],
"source": [
"def tokenize_function(examples):\n",
" return tokenizer(examples[\"text\"], padding=\"max_length\", truncation=True)\n",
" return tokenizer(\n",
" examples[\"text\"],\n",
" padding=\"max_length\",\n",
" truncation=True,\n",
" )\n",
"\n",
"\n",
"tokenized_datasets = raw_datasets.map(tokenize_function, batched=True)"
Expand Down Expand Up @@ -314,19 +320,11 @@
")\n",
"trainer.train()"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"collapsed_sections": [],
"name": "Comet with Hugging Face",
"provenance": []
},
Expand All @@ -345,9 +343,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.3"
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 1
"nbformat_minor": 4
}
2 changes: 1 addition & 1 deletion ...grations/model-training/hugging_face/transformers-distilbert-fine-tuning/requirements.txt
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Expand Up @@ -3,4 +3,4 @@ comet_ml
pandas
scikit-learn
torch
transformers
transformers<4.40.0
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