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
Browse files- .gitattributes +1 -0
- README.md +9 -0
- config.json +54 -0
- generation_config.json +6 -0
- model.safetensors +3 -0
- preprocessor_config.json +15 -0
- tekken.json +3 -0
.gitattributes
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README.md
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---
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library_name: transformers
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tags:
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- trl
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---
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# Tiny VoxtralForConditionalGeneration
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This is a minimal model built for unit tests in the [TRL](https://github.com/huggingface/trl) library.
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config.json
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{
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"architectures": [
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"VoxtralForConditionalGeneration"
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],
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"audio_config": {
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"activation_dropout": 0.0,
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"activation_function": "gelu",
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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": 1280,
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"initializer_range": 0.02,
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"intermediate_size": 5120,
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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": 20,
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"num_hidden_layers": 32,
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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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"vocab_size": 51866
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},
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"audio_token_id": 24,
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"dtype": "bfloat16",
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"hidden_size": 3072,
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"model_type": "voxtral",
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"projector_hidden_act": "gelu",
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"text_config": {
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"attention_bias": false,
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"attention_dropout": 0.0,
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"head_dim": 4,
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"hidden_act": "silu",
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"hidden_size": 16,
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"initializer_range": 0.02,
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"intermediate_size": 32,
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"layer_types": null,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 4,
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"num_hidden_layers": 2,
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"num_key_value_heads": 2,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 100000000.0,
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"sliding_window": null,
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"use_cache": true,
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"vocab_size": 131072
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},
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"transformers_version": "4.56.2",
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"vocab_size": 131072
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}
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generation_config.json
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{
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"bos_token_id": 1,
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"eos_token_id": 2,
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"pad_token_id": 11,
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"transformers_version": "4.56.2"
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:ccef54545a1e5b005e5d5332b169749da57017aa2de3017f85ffff5a7f552a1d
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size 1282559192
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preprocessor_config.json
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{
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"chunk_length": 30,
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"dither": 0.0,
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"feature_extractor_type": "WhisperFeatureExtractor",
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"feature_size": 128,
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"hop_length": 160,
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"n_fft": 400,
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"n_samples": 480000,
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"nb_max_frames": 3000,
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"padding_side": "right",
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"padding_value": 0.0,
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"processor_class": "VoxtralProcessor",
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"return_attention_mask": false,
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"sampling_rate": 16000
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}
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tekken.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:4aaf3836c2a5332f029ce85a7a62255c966f47b6797ef81dedd0ade9c862e4a8
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size 14894206
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