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Wav2Vec2-integration

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Wav2Vec2-integration
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{
  "mic": "0.3",
  "name": "Wav2Vec2 CTC speech recognition",
  "usage": "Wav2Vec2Processor + Wav2Vec2ForCTC, greedy CTC decoding, batched",
  "architecture": "Wav2Vec2ForCTC",
  "checkpoints": {
    "facebook/wav2vec2-base-960h": {
      "fixture": "hf-internal-testing/mic-wav2vec2-base-960h-slim"
    }
  },
  "fixtures": {
    "hf-internal-testing/mic-wav2vec2-base-960h-slim": {
      "built_from": "facebook/wav2vec2-base-960h",
      "covers": [
        "facebook/wav2vec2-base-960h"
      ],
      "build": {
        "seed": 17,
        "accept_insensitive": {
          "input_values:halve": "Wav2Vec2-base's bias-free first convolution feeds a group norm, so at fixture size the output ignores input amplitude (5e-5, random or overfit); the real checkpoint moves by 3.9. Amplitude regressions need the real-checkpoint run."
        }
      }
    }
  },
  "integrations": {
    "transformers": {
      "entry_point": "integrations/transformers/usage.md",
      "format": "runnable-markdown",
      "requires": [
        "transformers>=5",
        "torch"
      ],
      "targets": [
        "fixtures",
        "checkpoints"
      ],
      "variants": {
        "default": {},
        "eager": {
          "attn_implementation": "eager"
        },
        "bfloat16": {
          "dtype": "bfloat16"
        }
      },
      "training": true,
      "resources": {
        "fixture": {
          "memory_gb": 1,
          "download_mb": 20
        },
        "facebook/wav2vec2-base-960h": {
          "memory_gb": 2,
          "download_mb": 378
        }
      }
    }
  },
  "outputs": {
    "runtime": {
      "compare": "exact"
    },
    "predicted_ids": {
      "compare": "exact"
    },
    "predicted_text": {
      "compare": "exact"
    },
    "logits": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "feature_extractor_config_keys": {
      "compare": "exact"
    },
    "training.loss": {
      "compare": "allclose",
      "atol": 0.0001,
      "rtol": 0.0001
    },
    "training.gradients": {
      "compare": "all_true"
    },
    "training.updated": {
      "compare": "true"
    }
  }
}