Instructions to use uracoder/llama-8b-jarvis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use uracoder/llama-8b-jarvis with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("uracoder/llama-8b-jarvis", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download config.json from uracoder/llama-8b-jarvis: direct link, hf CLI and curl.
- Browser
- Download file 689 Bytes
-
https://huggingface.co/uracoder/llama-8b-jarvis/resolve/main/config.json
- Command line
-
hf download hf://uracoder/llama-8b-jarvis/config.json
-
curl -L -o config.json https://huggingface.co/uracoder/llama-8b-jarvis/resolve/main/config.json
689 Bytes
| { | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 128000, | |
| "eos_token_id": 128001, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 8192, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": null, | |
| "rope_theta": 500000.0, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.55.4", | |
| "use_cache": true, | |
| "vocab_size": 128256 | |
| } | |