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Model: prithivMLmods/Llama-Song-Stream-3B-Instruct Source: Original Platform
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README.md
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---
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license: apache-2.0
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datasets:
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- prithivMLmods/Song-Catalogue-Long-Thought
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language:
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- en
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base_model:
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- meta-llama/Llama-3.2-3B-Instruct
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pipeline_tag: text-generation
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library_name: transformers
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tags:
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- safetensors
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- Llama3.2
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- 3B
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- Extended-Stream
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- text-generation-inference
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- Instruct
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---
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### **Llama-Song-Stream-3B-Instruct Model Card**
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The **Llama-Song-Stream-3B-Instruct** is a fine-tuned language model specializing in generating music-related text, such as song lyrics, compositions, and musical thoughts. Built upon the **meta-llama/Llama-3.2-3B-Instruct** base, it has been trained with a custom dataset focused on song lyrics and music compositions to produce context-aware, creative, and stylized music output.
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| **File Name** | **Size** | **Description** |
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|---------------------------------|------------|-------------------------------------------------|
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| `.gitattributes` | 1.57 kB | LFS tracking file to manage large model files. |
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| `README.md` | 282 Bytes | Documentation with model details and usage. |
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| `config.json` | 1.03 kB | Model configuration settings. |
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| `generation_config.json` | 248 Bytes | Generation parameters like max sequence length. |
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| `pytorch_model-00001-of-00002.bin` | 4.97 GB | Primary weights (part 1 of 2). |
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| `pytorch_model-00002-of-00002.bin` | 1.46 GB | Primary weights (part 2 of 2). |
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| `pytorch_model.bin.index.json` | 21.2 kB | Index file mapping the checkpoint layers. |
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| `special_tokens_map.json` | 477 Bytes | Defines special tokens for tokenization. |
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| `tokenizer.json` | 17.2 MB | Tokenizer data for text generation. |
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| `tokenizer_config.json` | 57.4 kB | Configuration settings for tokenization. |
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### **Key Features**
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1. **Song Generation:**
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- Generates full song lyrics based on user input, maintaining rhyme, meter, and thematic consistency.
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2. **Music Context Understanding:**
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- Trained on lyrics and song patterns to mimic and generate song-like content.
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3. **Fine-tuned Creativity:**
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- Fine-tuned using *Song-Catalogue-Long-Thought* for coherent lyric generation over extended prompts.
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4. **Interactive Text Generation:**
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- Designed for use cases like generating lyrical ideas, creating drafts for songwriters, or exploring themes musically.
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---
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### **Training Details**
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- **Base Model:** [meta-llama/Llama-3.2-3B-Instruct](#)
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- **Finetuning Dataset:** [prithivMLmods/Song-Catalogue-Long-Thought](#)
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- This dataset comprises 57.7k examples of lyrical patterns, song fragments, and themes.
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---
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### **Applications**
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1. **Songwriting AI Tools:**
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- Generate lyrics for genres like pop, rock, rap, classical, and others.
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2. **Creative Writing Assistance:**
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- Assist songwriters by suggesting lyric variations and song drafts.
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3. **Storytelling via Music:**
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- Create song narratives using custom themes and moods.
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4. **Entertainment AI Integration:**
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- Build virtual musicians or interactive lyric-based content generators.
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---
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### **Example Usage**
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#### **Setup**
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First, load the Llama-Song-Stream model:
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "prithivMLmods/Llama-Song-Stream-3B-Instruct"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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```
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---
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#### **Generate Lyrics Example**
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```python
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prompt = "Write a song about freedom and the open sky"
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(**inputs, max_length=100, temperature=0.7, num_return_sequences=1)
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generated_lyrics = tokenizer.decode(outputs[0], skip_special_tokens=True)
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print(generated_lyrics)
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```
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---
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### **Deployment Notes**
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1. **Serverless vs. Dedicated Endpoints:**
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The model currently does not have enough usage for a serverless endpoint. Options include:
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- **Dedicated inference endpoints** for faster responses.
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- **Custom integrations via Hugging Face inference tools.**
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2. **Resource Requirements:**
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Ensure sufficient GPU memory and compute for large PyTorch model weights.
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---
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config.json
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{
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"_name_or_path": "meta-llama/Llama-3.2-3B-Instruct",
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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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"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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"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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"rope_type": "llama3"
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"rope_theta": 500000.0,
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"tie_word_embeddings": true,
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"transformers_version": "4.46.3",
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"unsloth_version": "2024.12.4",
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"use_cache": true,
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"vocab_size": 128256
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}
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||||
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||||
23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
@@ -0,0 +1,23 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
}
|
||||
}
|
||||
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
BIN
tokenizer.json
(Stored with Git LFS)
Normal file
Binary file not shown.
2064
tokenizer_config.json
Normal file
2064
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user