Instructions to use utahnlp/laconic-1b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use utahnlp/laconic-1b with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, LlamaBiForMNTP tokenizer = AutoTokenizer.from_pretrained("utahnlp/laconic-1b") model = LlamaBiForMNTP.from_pretrained("utahnlp/laconic-1b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from utahnlp/laconic-1b: direct link, hf CLI and curl.
- Browser
- Download file 835 Bytes
-
https://huggingface.co/utahnlp/laconic-1b/resolve/main/config.json
- Command line
-
hf download hf://utahnlp/laconic-1b/config.json
-
curl -L -o config.json https://huggingface.co/utahnlp/laconic-1b/resolve/main/config.json
835 Bytes
| { | |
| "architectures": [ | |
| "LlamaBiForMNTP" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 128000, | |
| "eos_token_id": 128001, | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 8192, | |
| "max_position_embeddings": 131072, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 16, | |
| "num_key_value_heads": 8, | |
| "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, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.51.3", | |
| "use_cache": true, | |
| "vocab_size": 128256 | |
| } | |