checkpoint update
Browse files- config.json +6 -1
- model.py +1 -0
config.json
CHANGED
@@ -1,13 +1,18 @@
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{
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"audio_enc_dim": 1024,
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"audio_encoder_name": "microsoft/wavlm-large",
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"audio_processor_name": "microsoft/wavlm-base",
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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": "4.41.2"
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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": 1024,
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"audio_encoder_name": "microsoft/wavlm-large",
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"audio_processor_name": "microsoft/wavlm-base",
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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": "4.41.2"
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}
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model.py
CHANGED
@@ -114,6 +114,7 @@ Output:'''
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out = self.llm_model.generate(
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inputs_embeds=combined_embeds,
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max_new_tokens=max_new_tokens,
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).cpu().tolist()[0]
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output_text = self.llm_tokenizer.decode(out, skip_special_tokens=True)
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out = self.llm_model.generate(
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inputs_embeds=combined_embeds,
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max_new_tokens=max_new_tokens,
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pad_token_id=self.llm_tokenizer.pad_token_id
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).cpu().tolist()[0]
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output_text = self.llm_tokenizer.decode(out, skip_special_tokens=True)
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