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Model: mesolitica/Malaysian-orpheus-3b-0.1-ft Source: Original Platform
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README.md
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---
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library_name: transformers
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base_model:
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- canopylabs/orpheus-3b-0.1-ft
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---
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# Malaysian canopylabs/orpheus-3b-0.1-ft
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Finetune [canopylabs/orpheus-3b-0.1-ft](https://huggingface.co/canopylabs/orpheus-3b-0.1-ft) on standard Malay and minimal Mandarin.
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## Training session
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Finetune on [Mesolitica/TTS](https://huggingface.co/datasets/mesolitica/TTS) to make the model able to generate Malay voice with minimal Mandarin.
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## How we train
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1. LoRA on `["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj", "embed_tokens", "lm_head"]`.
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2. 128 Rank with alpha 256, or alpha of 2.0, but during merging, we use 1.5 ratio.
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3. Multipacking with proper SDPA causal masking to prevent document contamination and also make sure proper position ids.
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4. Chunk CE loss to reduce memory.
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Wandb at https://wandb.ai/huseinzol05/malay-orpheus-3b-0.1-ft-lora-128/workspace?nw=nwuserhuseinzol05
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## Example
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Load the model,
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer
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from snac import SNAC
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import torch
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import IPython.display as ipd
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def redistribute_codes(row):
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row_length = row.size(0)
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new_length = (row_length // 7) * 7
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trimmed_row = row[:new_length]
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code_list = [t - 128266 for t in trimmed_row]
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layer_1 = []
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layer_2 = []
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layer_3 = []
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for i in range((len(code_list)+1)//7):
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layer_1.append(code_list[7*i][None])
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layer_2.append(code_list[7*i+1][None]-4096)
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layer_3.append(code_list[7*i+2][None]-(2*4096))
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layer_3.append(code_list[7*i+3][None]-(3*4096))
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layer_2.append(code_list[7*i+4][None]-(4*4096))
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layer_3.append(code_list[7*i+5][None]-(5*4096))
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layer_3.append(code_list[7*i+6][None]-(6*4096))
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with torch.no_grad():
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codes = [torch.concat(layer_1),
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torch.concat(layer_2),
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torch.concat(layer_3)]
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for i in range(len(codes)):
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codes[i][codes[i] < 0] = 0
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codes[i] = codes[i][None]
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audio_hat = snac_model.decode(codes)
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return audio_hat.cpu()[0, 0]
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snac_model = SNAC.from_pretrained("hubertsiuzdak/snac_24khz")
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snac_model = snac_model.to("cuda")
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tokenizer = AutoTokenizer.from_pretrained('mesolitica/Malaysian-orpheus-3b-0.1-ft')
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model = AutoModelForCausalLM.from_pretrained(
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'mesolitica/Malaysian-orpheus-3b-0.1-ft', torch_dtype = torch.bfloat16
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).cuda()
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speakers = [
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'Husein',
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'Shafiqah Idayu',
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'Anwar Ibrahim',
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'KP'
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]
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speaker = speakers[0]
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text = 'Nama saya Husein, saya tak suka nasi ayam dan tak suka mandi, Xiàn zài wǒ yǒu bing chilling Wǒ hěn xǐ huān bing chilling.'
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prompt = f'<custom_token_3><|begin_of_text|>{speaker}: {text}<|eot_id|><custom_token_4><custom_token_5><custom_token_1>'
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input_ids = tokenizer(prompt,add_special_tokens = False, return_tensors = 'pt').to('cuda')
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with torch.no_grad():
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generated_ids = model.generate(
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**input_ids,
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max_new_tokens=1200,
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do_sample=True,
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temperature=0.9,
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top_p=0.8,
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repetition_penalty=1.1,
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num_return_sequences=1,
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eos_token_id=128258,
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)
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row = generated_ids[0, input_ids['input_ids'].shape[1]:]
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y_ = redistribute_codes(row)
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ipd.Audio(y_, rate = 24000)
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```
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<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/5e73316106936008a9ee6523/NIOtl7B6Myw1eBd5Lf76l.wav"></audio>
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## Source code
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Source code at https://github.com/mesolitica/malaya-speech/tree/master/session/orpheus
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config.json
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{
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"_name_or_path": "canopylabs/orpheus-3b-0.1-ft",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128001,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 3072,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
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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": 24,
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"num_hidden_layers": 28,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 32.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.47.1",
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"use_cache": true,
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"vocab_size": 156940
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}
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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generation_config.json
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.47.1"
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}
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19
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19
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Normal file
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3
tokenizer.json
Normal file
3
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Normal file
3
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Reference in New Issue
Block a user