Instructions to use trl-internal-testing/tiny-VoxtralForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trl-internal-testing/tiny-VoxtralForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="trl-internal-testing/tiny-VoxtralForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("trl-internal-testing/tiny-VoxtralForConditionalGeneration") model = AutoModelForSpeechSeq2Seq.from_pretrained("trl-internal-testing/tiny-VoxtralForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
Upload VoxtralForConditionalGeneration
#2
by qgallouedec HF Staff - opened
- config.json +4 -4
- model.safetensors +2 -2
config.json
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"attention_dropout": 0.0,
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"dropout": 0.0,
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"head_dim": 64,
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"hidden_size":
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"initializer_range": 0.02,
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"intermediate_size":
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"layerdrop": 0.0,
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"max_source_positions": 1500,
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"model_type": "voxtral_encoder",
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"num_attention_heads":
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"num_hidden_layers":
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"num_key_value_heads": 20,
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"num_mel_bins": 128,
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"scale_embedding": false,
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"attention_dropout": 0.0,
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"dropout": 0.0,
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"head_dim": 64,
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"hidden_size": 16,
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"initializer_range": 0.02,
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"intermediate_size": 64,
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"layerdrop": 0.0,
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"max_source_positions": 1500,
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"model_type": "voxtral_encoder",
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"num_attention_heads": 4,
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"num_hidden_layers": 2,
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"num_key_value_heads": 20,
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"num_mel_bins": 128,
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"scale_embedding": false,
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model.safetensors
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