initial_commit

README.md

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+---
+language: 
+- en
+- sp
+- ja
+- pe
+- hi
+- fr
+- ch
+- be
+- gu
+- ge
+- te
+- it
+- ar
+- po
+- ta
+- ma
+- ma
+- or
+- pa
+- po
+- ur
+- ga
+- he
+- ko
+- ca
+- th
+- du
+- in
+- vi
+- bu
+- fi
+- ce
+- la
+- tu
+- ru
+- cr
+- sw
+- yo
+- ku
+- bu
+- ma
+- cz
+- fi
+- so
+- ta
+- sw
+- si
+- ka
+- zh
+- ig
+- xh
+- ro
+- ha
+- es
+- sl
+- li
+- gr
+- ne
+- as
+- no
+
+widget:
+- text: "Translate to German:  My name is Arthur"
+  example_title: "Translation"
+- text: "Please answer to the following question. Who is going to be the next Ballon d'or?"
+  example_title: "Question Answering"
+- text: "Q: Can Geoffrey Hinton have a conversation with George Washington? Give the rationale before answering."
+  example_title: "Logical reasoning"
+- text: "Please answer the following question. What is the boiling point of Nitrogen?"
+  example_title: "Scientific knowledge"
+- text: "Answer the following yes/no question. Can you write a whole Haiku in a single tweet?"
+  example_title: "Yes/no question"
+- text: "Answer the following yes/no question by reasoning step-by-step. Can you write a whole Haiku in a single tweet?"
+  example_title: "Reasoning task"
+- text: "Q: ( False or not False or False ) is? A: Let's think step by step"
+  example_title: "Boolean Expressions"
+- text: "The square root of x is the cube root of y. What is y to the power of 2, if x = 4?"
+  example_title: "Math reasoning"
+- text: "Premise:  At my age you will probably have learnt one lesson. Hypothesis:  It's not certain how many lessons you'll learn by your thirties. Does the premise entail the hypothesis?"
+  example_title: "Premise and hypothesis"
+
+tags:
+- text2text-generation
+
+datasets:
+- svakulenk0/qrecc
+- taskmaster2
+- djaym7/wiki_dialog
+- deepmind/code_contests
+- lambada
+- gsm8k
+- aqua_rat
+- esnli
+- quasc
+- qed
+- financial_phrasebank
+
+
+license: apache-2.0
+---
+
+# Model Card for LoRA-FLAN-T5 large
+
+![model image](https://s3.amazonaws.com/moonup/production/uploads/1666363435475-62441d1d9fdefb55a0b7d12c.png)
+
+This repository contains the LoRA (Low Rank Adapters) of `flan-t5-large` that has been fine-tuned on [`financial_phrasebank`](https://huggingface.co/datasets/financial_phrasebank) dataset.
+
+## Usage
+
+Use this adapter with `peft` library
+
+```python
+# pip install peft transformers
+import torch
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+peft_model_id = "ybelkada/flan-t5-large-financial-phrasebank-lora"
+config = PeftConfig.from_pretrained(peft_model_id)
+
+model = AutoModelForSeq2SeqLM.from_pretrained(
+    config.base_model_name_or_path, 
+    torch_dtype='auto', 
+    device_map='auto'
+)
+tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
+
+# Load the Lora model
+model = PeftModel.from_pretrained(model, peft_model_id)
+```
+
+Enjoy!

adapter_config.json

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+{
+  "base_model_name_or_path": "google/flan-t5-large",
+  "bias": "none",
+  "enable_lora": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "lora_alpha": 32,
+  "lora_dropout": 0.05,
+  "merge_weights": false,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 16,
+  "target_modules": [
+    "q",
+    "v"
+  ],
+  "task_type": "SEQ_2_SEQ_LM"
+}

adapter_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b120d54fc8ce458aa90768fa0e56d03b4061b606b51ec8b8be8c17906094a570
+size 18980429