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Added model

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  1. README.md +81 -0
  2. config.json +55 -0
  3. pytorch_model.bin +3 -0
README.md ADDED
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+ ---
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+ language:
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+ - en
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+ tags:
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+ - question-answering
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+ - summarization
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+ - emotion-detection
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+ license: Apache 2.0
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+ datasets:
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+ - coqa
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+ - squad_v2
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+ - go_emotions
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+ - cnn_dailymail
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+ metrics:
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+ - f1
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+ ---
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+ # T5 Base with QA + Summary + Emotion
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+
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+ ## Description
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+
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+ This model was finetuned on the CoQa, Squad 2, GoEmotions and CNN/DailyMail.
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+
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+ It achieves a score of *F1 76.7* on the Squad 2 dev set and a score of *F1 68.5* on the CoQa dev set.
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+
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+ Summarisation and emotion detection has not been evaluated yet.
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+
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+ ## Usage
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+
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+ ### Question answering
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+
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+ ```python
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+ from transformers import T5ForConditionalGeneration, T5Tokenizer
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+ model = T5ForConditionalGeneration.from_pretrained("kiri-ai/t5-base-qa-summary-emotion")
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+ tokenizer = T5Tokenizer.from_pretrained("t5-base")
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+
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+ def get_answer(question, prev_qa, context):
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+ input_text = [f"q: {qa[0]} a: {qa[1]}" for qa in prev_qa]
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+ input_text.append(f"q: {question}")
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+ input_text.append(f"c: {context}")
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+ input_text = " ".join(input_text)
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+ features = tokenizer([input_text], return_tensors='pt')
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+ tokens = model.generate(input_ids=features['input_ids'],
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+ attention_mask=features['attention_mask'], max_length=64)
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+ return tokenizer.decode(tokens[0], skip_special_tokens=True)
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+
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+ print(get_answer("Why is the moon yellow?", "I'm not entirely sure why the moon is yellow.")) # unknown
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+
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+ context = "Elon Musk left OpenAI to avoid possible future conflicts with his role as CEO of Tesla."
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+
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+ print(get_answer("Why not?", [("Does Elon Musk still work with OpenAI", "No")], context)) # to avoid possible future conflicts with his role as CEO of Tesla
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+ ```
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+
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+ ### Summarisation
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+
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+ ```python
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+ from transformers import T5ForConditionalGeneration, T5Tokenizer
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+ model = T5ForConditionalGeneration.from_pretrained("kiri-ai/t5-base-qa-summary-emotion")
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+ tokenizer = T5Tokenizer.from_pretrained("t5-base")
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+
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+ def summary(context):
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+ input_text = f"summarize: {context}"
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+ features = tokenizer([input_text], return_tensors='pt')
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+ tokens = model.generate(input_ids=features['input_ids'],
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+ attention_mask=features['attention_mask'], max_length=64)
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+ return tokenizer.decode(tokens[0], skip_special_tokens=True)
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+ ```
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+
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+ ### Emotion detection
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+
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+ ```python
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+ from transformers import T5ForConditionalGeneration, T5Tokenizer
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+ model = T5ForConditionalGeneration.from_pretrained("kiri-ai/t5-base-qa-summary-emotion")
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+ tokenizer = T5Tokenizer.from_pretrained("t5-base")
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+
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+ def emotion(context):
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+ input_text = f"emotion: {context}"
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+ features = tokenizer([input_text], return_tensors='pt')
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+ tokens = model.generate(input_ids=features['input_ids'],
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+ attention_mask=features['attention_mask'], max_length=64)
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+ return tokenizer.decode(tokens[0], skip_special_tokens=True)
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "t5-base",
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+ "architectures": [
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+ "T5ForConditionalGeneration"
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+ ],
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+ "d_ff": 3072,
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+ "d_kv": 64,
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+ "d_model": 768,
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+ "decoder_start_token_id": 0,
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+ "dropout_rate": 0.1,
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+ "eos_token_id": 1,
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+ "feed_forward_proj": "relu",
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+ "initializer_factor": 1.0,
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+ "is_encoder_decoder": true,
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+ "layer_norm_epsilon": 1e-06,
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+ "model_type": "t5",
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+ "n_positions": 512,
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+ "num_decoder_layers": 12,
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+ "num_heads": 12,
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+ "num_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "relative_attention_num_buckets": 32,
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+ "task_specific_params": {
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+ "summarization": {
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+ "early_stopping": true,
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+ "length_penalty": 2.0,
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+ "max_length": 200,
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+ "min_length": 30,
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+ "no_repeat_ngram_size": 3,
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+ "num_beams": 4,
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+ "prefix": "summarize: "
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+ },
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+ "translation_en_to_de": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to German: "
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+ },
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+ "translation_en_to_fr": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to French: "
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+ },
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+ "translation_en_to_ro": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to Romanian: "
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+ }
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+ },
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+ "use_cache": true,
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+ "vocab_size": 32128
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+ }
pytorch_model.bin ADDED
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