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T5-integration

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T5-integration
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{
  "mic": "0.3",
  "name": "T5 text-to-text generation",
  "usage": "AutoTokenizer + AutoModelForSeq2SeqLM.generate, batched",
  "architecture": "T5ForConditionalGeneration, UMT5ForConditionalGeneration",
  "checkpoints": {
    "google-t5/t5-small": {
      "fixture": "hf-internal-testing/mic-t5-small-slim"
    },
    "google/umt5-small": {
      "fixture": "hf-internal-testing/mic-umt5-small-slim"
    }
  },
  "fixtures": {
    "hf-internal-testing/mic-t5-small-slim": {
      "built_from": "google-t5/t5-small",
      "covers": [
        "google-t5/t5-small"
      ],
      "build": {
        "seed": 17
      }
    },
    "hf-internal-testing/mic-umt5-small-slim": {
      "built_from": "google/umt5-small",
      "covers": [
        "google/umt5-small"
      ],
      "build": {
        "seed": 17,
        "model_class": "UMT5ForConditionalGeneration"
      }
    }
  },
  "integrations": {
    "transformers": {
      "entry_point": "integrations/transformers/usage.md",
      "format": "runnable-markdown",
      "requires": [
        "transformers>=5",
        "torch",
        "sentencepiece"
      ],
      "targets": [
        "fixtures",
        "checkpoints"
      ],
      "unsupported": {
        "google/umt5-small": "config.json has no model_type, so AutoModelForSeq2SeqLM cannot load it; the fixture (saved with model_type umt5) covers the UMT5 code path"
      },
      "variants": {
        "default": {},
        "eager": {
          "attn_implementation": "eager"
        },
        "bfloat16": {
          "dtype": "bfloat16"
        }
      },
      "training": true,
      "resources": {
        "fixture": {
          "memory_gb": 1,
          "download_mb": 150
        },
        "google-t5/t5-small": {
          "memory_gb": 1,
          "download_mb": 242
        }
      }
    }
  },
  "outputs": {
    "runtime": {
      "compare": "exact"
    },
    "generated_tokens": {
      "compare": "exact"
    },
    "generated_text": {
      "compare": "exact"
    },
    "label_logprobs": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "decoded_roundtrip": {
      "compare": "exact"
    },
    "training.loss": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "training.gradients": {
      "compare": "all_true"
    },
    "training.updated": {
      "compare": "true"
    }
  }
}