Text-to-Speech
Transformers
Safetensors
English
llama
text-generation
text-generation-inference
4-bit precision
Instructions to use saftle/maya1-nf4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saftle/maya1-nf4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="saftle/maya1-nf4")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("saftle/maya1-nf4") model = AutoModelForCausalLM.from_pretrained("saftle/maya1-nf4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 128000, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 128009, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 3072, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 8192, | |
| "max_position_embeddings": 131072, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 24, | |
| "num_hidden_layers": 28, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 128263, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "factor": 32.0, | |
| "high_freq_factor": 4.0, | |
| "low_freq_factor": 1.0, | |
| "original_max_position_embeddings": 8192, | |
| "rope_type": "llama3" | |
| }, | |
| "rope_theta": 500000.0, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "4.57.1", | |
| "use_cache": false, | |
| "vocab_size": 156960, | |
| "quantization_config": { | |
| "load_in_4bit": true, | |
| "load_in_8bit": false, | |
| "bnb_4bit_quant_type": "nf4", | |
| "bnb_4bit_compute_dtype": "bfloat16", | |
| "bnb_4bit_use_double_quant": true | |
| } | |
| } |