Prediction

Model

cjwbw/lorahub:02a0166b

ID

ujqqyibbie76zmqgtx4fbsx7gm

Status

Succeeded

Source

Web

Hardware

T4

Total duration

2m 31s

Created

over 2 years ago by chenxwh

Webhook

–

Input

example_inputs: Infer the date from context. Q: Today, 8/3/1997, is a day that we will never forget. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 03/27/1998 (B) 09/02/1997 (C) 07/27/1997 (D) 06/29/1997 (E) 07/27/1973 (F) 12/27/1997 A: Infer the date from context. Q: May 6, 1992 is like yesterday to Jane, but that is actually ten years ago. What is the date tomorrow in MM/DD/YYYY? Options: (A) 04/16/2002 (B) 04/07/2003 (C) 05/07/2036 (D) 05/28/2002 (E) 05/07/2002 A: Infer the date from context. Q: Today is the second day of the third month of 1966. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 02/26/1966 (B) 01/13/1966 (C) 02/02/1966 (D) 10/23/1966 (E) 02/23/1968 (F) 02/23/1966 A:
example_outputs: (C) (E) (F)
num_random_lora_modules: 20
max_inference_step: 40

{
  "example_inputs": "Infer the date from context.  Q: Today, 8/3/1997, is a day that we will never forget. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 03/27/1998 (B) 09/02/1997 (C) 07/27/1997 (D) 06/29/1997 (E) 07/27/1973 (F) 12/27/1997 A:\nInfer the date from context.  Q: May 6, 1992 is like yesterday to Jane, but that is actually ten years ago. What is the date tomorrow in MM/DD/YYYY? Options: (A) 04/16/2002 (B) 04/07/2003 (C) 05/07/2036 (D) 05/28/2002 (E) 05/07/2002 A:\nInfer the date from context.  Q: Today is the second day of the third month of 1966. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 02/26/1966 (B) 01/13/1966 (C) 02/02/1966 (D) 10/23/1966 (E) 02/23/1968 (F) 02/23/1966 A:",
  "example_outputs": "(C)\n(E)\n(F)",
  "max_inference_step": 40,
  "num_random_lora_modules": 20
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_TQU**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";
import fs from "node:fs";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run cjwbw/lorahub using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "cjwbw/lorahub:02a0166b0b1deeec3e794ced2dc6c670592302e158c9ec51b676279afd0e6238",
  {
    input: {
      example_inputs: "Infer the date from context.  Q: Today, 8/3/1997, is a day that we will never forget. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 03/27/1998 (B) 09/02/1997 (C) 07/27/1997 (D) 06/29/1997 (E) 07/27/1973 (F) 12/27/1997 A:\nInfer the date from context.  Q: May 6, 1992 is like yesterday to Jane, but that is actually ten years ago. What is the date tomorrow in MM/DD/YYYY? Options: (A) 04/16/2002 (B) 04/07/2003 (C) 05/07/2036 (D) 05/28/2002 (E) 05/07/2002 A:\nInfer the date from context.  Q: Today is the second day of the third month of 1966. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 02/26/1966 (B) 01/13/1966 (C) 02/02/1966 (D) 10/23/1966 (E) 02/23/1968 (F) 02/23/1966 A:",
      example_outputs: "(C)\n(E)\n(F)",
      max_inference_step: 40,
      num_random_lora_modules: 20
    }
  }
);

// To access the file URL:
console.log(output.url()); //=> "http://example.com"

// To write the file to disk:
fs.writeFile("my-image.png", output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_TQU**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run cjwbw/lorahub using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "cjwbw/lorahub:02a0166b0b1deeec3e794ced2dc6c670592302e158c9ec51b676279afd0e6238",
    input={
        "example_inputs": "Infer the date from context.  Q: Today, 8/3/1997, is a day that we will never forget. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 03/27/1998 (B) 09/02/1997 (C) 07/27/1997 (D) 06/29/1997 (E) 07/27/1973 (F) 12/27/1997 A:\nInfer the date from context.  Q: May 6, 1992 is like yesterday to Jane, but that is actually ten years ago. What is the date tomorrow in MM/DD/YYYY? Options: (A) 04/16/2002 (B) 04/07/2003 (C) 05/07/2036 (D) 05/28/2002 (E) 05/07/2002 A:\nInfer the date from context.  Q: Today is the second day of the third month of 1966. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 02/26/1966 (B) 01/13/1966 (C) 02/02/1966 (D) 10/23/1966 (E) 02/23/1968 (F) 02/23/1966 A:",
        "example_outputs": "(C)\n(E)\n(F)",
        "max_inference_step": 40,
        "num_random_lora_modules": 20
    }
)

# To access the file URL:
print(output.url())
#=> "http://example.com"

# To write the file to disk:
with open("my-image.png", "wb") as file:
    file.write(output.read())

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_TQU**********************************

This is your API token. Keep it to yourself.

Run cjwbw/lorahub using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "cjwbw/lorahub:02a0166b0b1deeec3e794ced2dc6c670592302e158c9ec51b676279afd0e6238",
    "input": {
      "example_inputs": "Infer the date from context.  Q: Today, 8/3/1997, is a day that we will never forget. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 03/27/1998 (B) 09/02/1997 (C) 07/27/1997 (D) 06/29/1997 (E) 07/27/1973 (F) 12/27/1997 A:\\nInfer the date from context.  Q: May 6, 1992 is like yesterday to Jane, but that is actually ten years ago. What is the date tomorrow in MM/DD/YYYY? Options: (A) 04/16/2002 (B) 04/07/2003 (C) 05/07/2036 (D) 05/28/2002 (E) 05/07/2002 A:\\nInfer the date from context.  Q: Today is the second day of the third month of 1966. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 02/26/1966 (B) 01/13/1966 (C) 02/02/1966 (D) 10/23/1966 (E) 02/23/1968 (F) 02/23/1966 A:",
      "example_outputs": "(C)\\n(E)\\n(F)",
      "max_inference_step": 40,
      "num_random_lora_modules": 20
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

Preview of application/octet-stream file unavailable

Download output

{
  "id": "ujqqyibbie76zmqgtx4fbsx7gm",
  "model": "cjwbw/lorahub",
  "version": "02a0166b0b1deeec3e794ced2dc6c670592302e158c9ec51b676279afd0e6238",
  "input": {
    "example_inputs": "Infer the date from context.  Q: Today, 8/3/1997, is a day that we will never forget. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 03/27/1998 (B) 09/02/1997 (C) 07/27/1997 (D) 06/29/1997 (E) 07/27/1973 (F) 12/27/1997 A:\nInfer the date from context.  Q: May 6, 1992 is like yesterday to Jane, but that is actually ten years ago. What is the date tomorrow in MM/DD/YYYY? Options: (A) 04/16/2002 (B) 04/07/2003 (C) 05/07/2036 (D) 05/28/2002 (E) 05/07/2002 A:\nInfer the date from context.  Q: Today is the second day of the third month of 1966. What is the date one week ago from today in MM/DD/YYYY? Options: (A) 02/26/1966 (B) 01/13/1966 (C) 02/02/1966 (D) 10/23/1966 (E) 02/23/1968 (F) 02/23/1966 A:",
    "example_outputs": "(C)\n(E)\n(F)",
    "max_inference_step": 40,
    "num_random_lora_modules": 20
  },
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19.0M/19.0M [00:00<00:00, 133MB/s]\n> Loading lorahub/flan_t5_large-adversarial_qa_dbidaf_answer_the_following_q ...\n 90%|█████████ | 18/20 [00:21<00:02,  1.23s/it]\nDownloading (…)/adapter_config.json:   0%|          | 0.00/411 [00:00<?, ?B/s]\u001b[A\nDownloading (…)/adapter_config.json: 100%|██████████| 411/411 [00:00<00:00, 655kB/s]\nDownloading adapter_model.bin:   0%|          | 0.00/19.0M [00:00<?, ?B/s]\u001b[A\nDownloading adapter_model.bin:  55%|█████▌    | 10.5M/19.0M [00:00<00:00, 59.2MB/s]\u001b[A\nDownloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 73.8MB/s]\n> Loading lorahub/flan_t5_large-race_middle_Select_the_best_answer_generate_span_ ...\n 95%|█████████▌| 19/20 [00:22<00:01,  1.23s/it]\nDownloading (…)/adapter_config.json:   0%|          | 0.00/411 [00:00<?, ?B/s]\u001b[A\nDownloading (…)/adapter_config.json: 100%|██████████| 411/411 [00:00<00:00, 1.31MB/s]\nDownloading adapter_model.bin:   0%|          | 0.00/19.0M [00:00<?, ?B/s]\u001b[A\nDownloading adapter_model.bin:  55%|█████▌    | 10.5M/19.0M [00:00<00:00, 93.8MB/s]\u001b[A\nDownloading adapter_model.bin: 100%|██████████| 19.0M/19.0M [00:00<00:00, 107MB/s]\n100%|██████████| 20/20 [00:23<00:00,  1.12s/it]\n100%|██████████| 20/20 [00:23<00:00,  1.17s/it]\nRunning tokenizer on dataset:   0%|          | 0/3 [00:00<?, ? examples/s]\nRunning tokenizer on dataset: 100%|██████████| 3/3 [00:00<00:00, 112.81 examples/s]\n> Begin to perform gradient-free optimization ...\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.19794374704360962\n39 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.19664074103037515\n38 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.20196577151616416\n37 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.18949530760447184\n36 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.18646785974502564\n35 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.18851580699284873\n34 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.17956692457199097\n33 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.18219556013743082\n32 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.18811706304550171\n31 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.18308404684066773\n30 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.15466183026631675\n29 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.13169783075650532\n28 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.11195437947909037\n27 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.14315053780873618\n26 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.09870247999827067\n25 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.09308040221532185\n24 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.08350652158260345\n23 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.1701445213953654\n22 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.08785513858000438\n21 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.18224913199742637\n20 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.887497984568278\n19 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.20113089762185843\n18 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.08463106314341227\n17 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.179056189929146\n16 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.07683334509531657\n15 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.17642755043471342\n14 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.06571920676354828\n13 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.0742276668098602\n12 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.05183583021748306\n11 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.12994661993059228\n10 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.08364694323973731\n9 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.08870862409630972\n8 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.08821432639038829\n7 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.05691506158264563\n6 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.05956370060788695\n5 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.13098620907509662\n4 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.06969356769947482\n3 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.09138107303580391\n2 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.061673278693635536\n1 remaining budget and 0 running jobs\nLaunching 1 jobs with new suggestions\nUpdating fitness with value 0.045564029637715844\n0 remaining budget and 0 running jobs\nThe recommended weight set for the LoRA modules is:\n0.4984: lorahub/flan_t5_large-wmt16_translate_ro-en\n-0.2598: lorahub/flan_t5_large-anli_r2\n0.4774: lorahub/flan_t5_large-gem_e2e_nlg\n1.0626: lorahub/flan_t5_large-quartz_read_passage_below_choose\n0.0428: lorahub/flan_t5_large-wiki_qa_Decide_good_answer\n0.4685: lorahub/flan_t5_large-race_high_Select_the_best_answer_no_instructions_\n-0.0285: lorahub/flan_t5_large-app_reviews_convert_to_rating\n-0.0458: lorahub/flan_t5_large-glue_mnli\n-0.0571: lorahub/flan_t5_large-sentiment140\n0.5707: lorahub/flan_t5_large-quail_context_description_question_answer_id\n0.5296: lorahub/flan_t5_large-snli\n0.3255: lorahub/flan_t5_large-dbpedia_14_pick_one_category_for_the_following_text\n-0.0600: lorahub/flan_t5_large-quac\n0.5097: lorahub/flan_t5_large-quoref_What_Is_The_Answer\n0.5041: lorahub/flan_t5_large-wiqa_what_might_be_the_last_step_of_the_process\n0.5070: lorahub/flan_t5_large-super_glue_cb\n-0.1103: lorahub/flan_t5_large-quarel_heres_a_story\n-0.0032: lorahub/flan_t5_large-race_middle_Is_this_the_right_answer\n-0.0723: lorahub/flan_t5_large-adversarial_qa_dbidaf_answer_the_following_q\n0.0988: lorahub/flan_t5_large-race_middle_Select_the_best_answer_generate_span_",
  "output": "https://replicate.delivery/pbxt/ICinfYhrpdRyeEMt78Za2IkPAh0751Lf1uLvBjX5pWFl8ssiA/out.bin",
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2023-08-03T14:09:35.629561Z",
  "started_at": "2023-08-03T14:09:39.958746Z",
  "completed_at": "2023-08-03T14:12:06.138705Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/ujqqyibbie76zmqgtx4fbsx7gm/cancel",
    "get": "https://api.replicate.com/v1/predictions/ujqqyibbie76zmqgtx4fbsx7gm"
  },
  "metrics": {
    "predict_time": 146.179959,
    "total_time": 150.509144
  }
}

Generated in

2 minutes 26 seconds

Tweak it Report

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Launching 1 jobs with new suggestions Updating fitness with value 0.19794374704360962 39 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.19664074103037515 38 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.20196577151616416 37 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18949530760447184 36 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18646785974502564 35 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18851580699284873 34 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.17956692457199097 33 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18219556013743082 32 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18811706304550171 31 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18308404684066773 30 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.15466183026631675 29 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.13169783075650532 28 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.11195437947909037 27 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.14315053780873618 26 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.09870247999827067 25 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.09308040221532185 24 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08350652158260345 23 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.1701445213953654 22 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08785513858000438 21 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.18224913199742637 20 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.887497984568278 19 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.20113089762185843 18 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08463106314341227 17 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.179056189929146 16 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.07683334509531657 15 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.17642755043471342 14 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.06571920676354828 13 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.0742276668098602 12 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.05183583021748306 11 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.12994661993059228 10 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08364694323973731 9 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08870862409630972 8 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.08821432639038829 7 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.05691506158264563 6 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.05956370060788695 5 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.13098620907509662 4 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.06969356769947482 3 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.09138107303580391 2 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.061673278693635536 1 remaining budget and 0 running jobs Launching 1 jobs with new suggestions Updating fitness with value 0.045564029637715844 0 remaining budget and 0 running jobs The recommended weight set for the LoRA modules is: 0.4984: lorahub/flan_t5_large-wmt16_translate_ro-en -0.2598: lorahub/flan_t5_large-anli_r2 0.4774: lorahub/flan_t5_large-gem_e2e_nlg 1.0626: lorahub/flan_t5_large-quartz_read_passage_below_choose 0.0428: lorahub/flan_t5_large-wiki_qa_Decide_good_answer 0.4685: lorahub/flan_t5_large-race_high_Select_the_best_answer_no_instructions_ -0.0285: lorahub/flan_t5_large-app_reviews_convert_to_rating -0.0458: lorahub/flan_t5_large-glue_mnli -0.0571: lorahub/flan_t5_large-sentiment140 0.5707: lorahub/flan_t5_large-quail_context_description_question_answer_id 0.5296: lorahub/flan_t5_large-snli 0.3255: lorahub/flan_t5_large-dbpedia_14_pick_one_category_for_the_following_text -0.0600: lorahub/flan_t5_large-quac 0.5097: lorahub/flan_t5_large-quoref_What_Is_The_Answer 0.5041: lorahub/flan_t5_large-wiqa_what_might_be_the_last_step_of_the_process 0.5070: lorahub/flan_t5_large-super_glue_cb -0.1103: lorahub/flan_t5_large-quarel_heres_a_story -0.0032: lorahub/flan_t5_large-race_middle_Is_this_the_right_answer -0.0723: lorahub/flan_t5_large-adversarial_qa_dbidaf_answer_the_following_q 0.0988: lorahub/flan_t5_large-race_middle_Select_the_best_answer_generate_span_