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Dockerfile.txt ADDED
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+ # Imagen base
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+ FROM python:3.9-slim
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+
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+ # Establecer directorio de trabajo
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+ WORKDIR /code
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+
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+ # Instalar git y otras dependencias básicas del sistema
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+ RUN apt-get update && apt-get install -y git && apt-get clean
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+
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+ # Copiar todos los archivos del Space
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+ COPY . .
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+
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+ # Instalar dependencias de Python
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+ RUN pip install --upgrade pip
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+ RUN pip install -r requirements.txt
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+
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+ # Exponer el puerto (7860 para Spaces)
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+ EXPOSE 7860
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+
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+ # Comando para iniciar FastAPI con Uvicorn
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+ CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
MarIA/config.json ADDED
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+ {
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+ "architectures": [
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+ "RobertaForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.0,
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+ "bos_token_id": 0,
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+ "classifier_dropout": null,
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+ "eos_token_id": 2,
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+ "gradient_checkpointing": false,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.0,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "LABEL_0",
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+ "1": "LABEL_1",
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+ "2": "LABEL_2"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "LABEL_0": 0,
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+ "LABEL_1": 1,
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+ "LABEL_2": 2
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+ },
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+ "layer_norm_eps": 1e-05,
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+ "max_position_embeddings": 514,
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+ "model_type": "roberta",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 1,
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+ "position_embedding_type": "absolute",
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+ "problem_type": "single_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.51.3",
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+ "type_vocab_size": 1,
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+ "use_cache": true,
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+ "vocab_size": 50262
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+ }
MarIA/merges.txt ADDED
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MarIA/special_tokens_map.json ADDED
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+ {
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+ "bos_token": {
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+ "content": "<s>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false
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+ },
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+ "cls_token": {
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+ "content": "<s>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false
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+ },
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+ "eos_token": {
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+ "content": "</s>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false
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+ },
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+ "mask_token": {
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+ "content": "<mask>",
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+ "lstrip": true,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false
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+ },
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+ "pad_token": {
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+ "content": "<pad>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false
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+ },
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+ "sep_token": {
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+ "content": "</s>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false
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+ },
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+ "unk_token": {
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+ "content": "<unk>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false
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+ }
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+ }
MarIA/tokenizer.json ADDED
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MarIA/tokenizer_config.json ADDED
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+ {
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+ "add_prefix_space": false,
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+ "added_tokens_decoder": {
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+ "0": {
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+ "content": "<s>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "1": {
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+ "content": "<pad>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "2": {
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+ "content": "</s>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "3": {
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+ "content": "<unk>",
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+ "lstrip": false,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ },
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+ "4": {
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+ "content": "<mask>",
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+ "lstrip": true,
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+ "normalized": true,
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+ "rstrip": false,
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+ "single_word": false,
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+ "special": true
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+ }
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+ },
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+ "bos_token": "<s>",
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+ "clean_up_tokenization_spaces": false,
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+ "cls_token": "<s>",
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+ "eos_token": "</s>",
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+ "errors": "replace",
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+ "extra_special_tokens": {},
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+ "mask_token": "<mask>",
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+ "max_len": 512,
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+ "model_max_length": 512,
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+ "pad_token": "<pad>",
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+ "sep_token": "</s>",
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+ "tokenizer_class": "RobertaTokenizer",
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+ "trim_offsets": true,
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+ "unk_token": "<unk>"
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+ }
MarIA/vocab.json ADDED
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app.py ADDED
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+ from fastapi import FastAPI
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+ from pydantic import BaseModel
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+ from transformers import pipeline
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+
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+ # Cargar modelo desde carpeta local
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+ pipe = pipeline("text-classification", model="./MarIA", tokenizer="./MarIA")
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+
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+ label_map = {
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+ "0": "Negativo",
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+ "1": "Neutral",
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+ "2": "Positivo"
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+ }
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+
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+ # FastAPI app
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+ app = FastAPI()
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+
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+ # Entrada de la API
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+ class TextInput(BaseModel):
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+ text: str
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+
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+ @app.post("/predict")
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+ def predict(input: TextInput):
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+ result = pipe(input.text)[0]
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+ label_id = result["label"]
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+ label_num = label_id.split("_")[-1] if "_" in label_id else label_id
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+ sentiment = label_map.get(label_num, "Desconocido")
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+ return {"sentiment": sentiment}
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+
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+
requirements.txt ADDED
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+ transformers
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+ torch
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+ fastapi
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+ uvicorn