Upload model
Browse files- config.json +6 -1
- model-00001-of-00002.safetensors +2 -2
- model-00002-of-00002.safetensors +2 -2
- model.py +3 -1
- model.safetensors.index.json +202 -510
config.json
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{
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"audio_enc_dim": 1280,
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"audio_encoder_name": "facebook/hubert-xlarge-ll60k",
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"audio_processor_name": "facebook/hubert-large-ls960-ft",
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"auto_map": {
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"AutoConfig": "config.SpeechLLMModelConfig"
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},
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"llm_dim": 2048,
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"llm_model_checkpoint": "hf_repo/llm_model_checkpoint",
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"llm_model_name": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
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"model_type": "custom_model",
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"transformers_version": "4.38.2"
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}
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{
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"architectures": [
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"SpeechLLMModel"
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],
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"audio_enc_dim": 1280,
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"audio_encoder_name": "facebook/hubert-xlarge-ll60k",
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"audio_processor_name": "facebook/hubert-large-ls960-ft",
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"auto_map": {
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"AutoConfig": "config.SpeechLLMModelConfig",
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"AutoModel": "model.SpeechLLMModel"
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},
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"llm_dim": 2048,
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"llm_model_checkpoint": "hf_repo/llm_model_checkpoint",
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"llm_model_name": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
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"model_type": "custom_model",
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"torch_dtype": "float32",
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"transformers_version": "4.38.2"
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}
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model-00001-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:18785830f9c696dfb288148f64e92b017789e290fbfdbffa4f8c03e903ed65b2
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size 4973217960
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model-00002-of-00002.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:fbc74aa8e2666342b54594419847adfa6279238c9416dda34a09202d00dd638f
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size 3395612080
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model.py
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@@ -48,13 +48,15 @@ class SpeechLLMModel(PreTrainedModel):
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task_type="CAUSAL_LM",
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)
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self.llm_model = get_peft_model(self.llm_model, peft_config)
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def encode(self, mel, pre_tokenized_ids, post_tokenized_ids, output_tokenized_ids):
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batch_size = mel.shape[0]
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with torch.no_grad():
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speech_embeds = self.audio_encoder(mel)
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embedder = self.llm_model.model.
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pre_prompt_embeds = embedder(pre_tokenized_ids)
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post_prompt_embeds = embedder(post_tokenized_ids)
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output_prompt_embeds = embedder(output_tokenized_ids)
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task_type="CAUSAL_LM",
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)
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self.llm_model = get_peft_model(self.llm_model, peft_config)
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self.llm_model = self.llm_model.merge_and_unload()
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def encode(self, mel, pre_tokenized_ids, post_tokenized_ids, output_tokenized_ids):
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batch_size = mel.shape[0]
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with torch.no_grad():
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speech_embeds = self.audio_encoder(mel)
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embedder = self.llm_model.model.embed_tokens
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pre_prompt_embeds = embedder(pre_tokenized_ids)
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post_prompt_embeds = embedder(post_tokenized_ids)
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output_prompt_embeds = embedder(output_tokenized_ids)
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model.safetensors.index.json
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{
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"metadata": {
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"total_size":
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},
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"weight_map": {
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"audio_encoder.cnn.1.bias": "model-00001-of-00002.safetensors",
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"audio_encoder.encoder.feature_projection.projection.bias": "model-00001-of-00002.safetensors",
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| 1019 |
}
|
| 1020 |
}
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