abhishek HF staff commited on
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Commit From AutoNLP

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.gitattributes CHANGED
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README.md ADDED
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+ ---
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+ tags:
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+ - autonlp
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+ - question-answering
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+ language: unk
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+ widget:
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+ - text: "Who loves AutoNLP?"
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+ context: "Everyone loves AutoNLP"
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+ datasets:
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+ - teacookies/autonlp-data-more_fine_tune_24465520
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+ co2_eq_emissions: 77.64468929470678
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+ ---
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+
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+ # Model Trained Using AutoNLP
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+
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+ - Problem type: Extractive Question Answering
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+ - Model ID: 26265910
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+ - CO2 Emissions (in grams): 77.64468929470678
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+
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+ ## Validation Metrics
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+
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+ - Loss: 5.950643062591553
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+
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+ ## Usage
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+
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+ You can use cURL to access this model:
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+
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+ ```
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+ $ curl -X POST -H "Authorization: Bearer YOUR_API_KEY" -H "Content-Type: application/json" -d '{"question": "Who loves AutoNLP?", "context": "Everyone loves AutoNLP"}' https://api-inference.huggingface.co/models/teacookies/autonlp-more_fine_tune_24465520-26265910
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+ ```
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+
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+ Or Python API:
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+
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+ ```
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+ import torch
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+
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+ from transformers import AutoModelForQuestionAnswering, AutoTokenizer
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+
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+ model = AutoModelForQuestionAnswering.from_pretrained("teacookies/autonlp-more_fine_tune_24465520-26265910", use_auth_token=True)
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+
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+ tokenizer = AutoTokenizer.from_pretrained("teacookies/autonlp-more_fine_tune_24465520-26265910", use_auth_token=True)
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+
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+ from transformers import BertTokenizer, BertForQuestionAnswering
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+
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+ question, text = "Who loves AutoNLP?", "Everyone loves AutoNLP"
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+
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+ inputs = tokenizer(question, text, return_tensors='pt')
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+
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+ start_positions = torch.tensor([1])
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+
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+ end_positions = torch.tensor([3])
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+
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+ outputs = model(**inputs, start_positions=start_positions, end_positions=end_positions)
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+
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+ loss = outputs.loss
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+
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+ start_scores = outputs.start_logits
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+
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+ end_scores = outputs.end_logits
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+ ```
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+ "_name_or_path": "AutoNLP",
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+ "XLMRobertaForQuestionAnswering"
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "language": "english",
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+ "max_position_embeddings": 514,
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+ "model_type": "xlm-roberta",
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+ "name": "XLMRoberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 1,
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+ "padding": "max_length",
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+ "position_embedding_type": "absolute",
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+ "transformers_version": "4.8.0",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 250002
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+ }
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