Update my_app.aiconfig.json

my_app.aiconfig.json

@@ -11,11 +11,11 @@
  "default_model": null,
  "model_parsers": null
  },
- "description": "In this notebook, we compare the individual performance of HF hosted LLMs () on a few example questions from the GLUE benchmarks (https://gluebenchmark.com/tasks).\n\nExample questions taken from \"What is the GLUE Benchmark\" medium post - https://angelina-yang.medium.com/what-is-the-glue-benchmark-for-nlu-systems-61127b3cab3f",
+ "description": "**In this notebook, we compare the individual performance of HF hosted LLMs () on a few example questions from the GLUE benchmarks (https://gluebenchmark.com/tasks).**\n\n**Example questions taken from \"What is the GLUE Benchmark\" medium post - https://angelina-yang.medium.com/what-is-the-glue-benchmark-for-nlu-systems-61127b3cab3f**\n\n---\n\n| General Language Understanding Evaluation (GLUE) Tasks | Example Question |\n| ----------- | ----------- |\n| Corpus of Linguistic Acceptability (CoLA) | Is the sentence grammatical or ungrammatical? \"This building is than that one.\" |\n| Stanford Sentiment Treebank (SST) | Is the movie review positive, negative, or neutral? \"The movie is funny, smart, visually inventive, and most of all, alive.\" |\n| Winograd NLI (WNLI) | Sentence B replaces sentence A's ambiguous pronoun with one of the nouns - is this the correct noun? \"A) Lily spoke to Donna, breaking her concentration. B) Lily spoke to Donna, breaking Lily's concentration.\" |",
  "prompts": [
  {
  "name": "mistral_7b_instruct_v0.1",
- "input": "{{SST_2_ex_prompt}}",
+ "input": "Is the movie review positive, negative, or neutral?\n\n\n\"The movie is funny, smart, visually inventive, and most of all, alive.\"",
  "metadata": {
  "model": {
  "name": "Text Generation",
@@ -27,11 +27,18 @@
  "parameters": {}
  },
  "outputs": [
+ {
+ "output_type": "execute_result",
+ "execution_count": 0,
+ "data": "\n\nThe movie review is positive.</s>",
+ "mime_type": null,
+ "metadata": {}
+ }
  ]
  },
  {
  "name": "google_flan_t5_sm",
- "input": "{{SST_2_ex_prompt}}",
+ "input": "Is the movie review positive, negative, or neutral?\n\n\"The movie is funny, smart, visually inventive, and most of all, alive.\"",
  "metadata": {
  "model": {
  "name": "Conversational",
@@ -45,6 +52,28 @@
  "parameters": {}
  },
  "outputs": [
+ {
+ "output_type": "execute_result",
+ "execution_count": 0,
+ "data": "positive",
+ "mime_type": null,
+ "metadata": {
+ "raw_response": {
+ "generated_text": "positive",
+ "conversation": {
+ "generated_responses": [
+ "positive"
+ ],
+ "past_user_inputs": [
+ "Is the movie review positive, negative, or neutral?\n\n\"The movie is funny, smart, visually inventive, and most of all, alive.\""
+ ]
+ },
+ "warnings": [
+ "\nNo chat template is defined for this tokenizer - using a default chat template that implements the ChatML format (without BOS/EOS tokens!). If the default is not appropriate for your model, please set `tokenizer.chat_template` to an appropriate template. See https://huggingface.co/docs/transformers/main/chat_templating for more information.\n"
+ ]
+ }
+ }
+ }
  ]
  },
  {
@@ -61,6 +90,25 @@
  "parameters": {}
  },
  "outputs": [
+ {
+ "output_type": "execute_result",
+ "execution_count": 0,
+ "data": "The movie review is positive.",
+ "mime_type": null,
+ "metadata": {
+ "raw_response": {
+ "generated_text": "The movie review is positive.",
+ "conversation": {
+ "generated_responses": [
+ "The movie review is positive."
+ ],
+ "past_user_inputs": [
+ "<|system|>\nYou are to answer the following question by the user</s>\n<|user|>\nIs the movie review positive, negative, or neutral?\n\n&quot;The movie is funny, smart, visually inventive, and most of all, alive.&quot;</s>\n<|assistant|>"
+ ]
+ }
+ }
+ }
+ }
  ]
  }
  ]