Instructions to use Gsj49/adaptiveG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Gsj49/adaptiveG with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Gsj49/adaptiveG", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download models/coding/fixed4/seed42/step500/config.json from Gsj49/adaptiveG: direct link, hf CLI and curl.
- Browser
- Download file 772 Bytes
-
https://huggingface.co/Gsj49/adaptiveG/resolve/main/models/coding/fixed4/seed42/step500/config.json
- Command line
-
hf download hf://Gsj49/adaptiveG/models/coding/fixed4/seed42/step500/config.json
-
curl -L -o config.json https://huggingface.co/Gsj49/adaptiveG/resolve/main/models/coding/fixed4/seed42/step500/config.json
772 Bytes
| { | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 32013, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 32014, | |
| "head_dim": 128, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 5504, | |
| "max_position_embeddings": 16384, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "num_key_value_heads": 16, | |
| "pad_token_id": 32014, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": { | |
| "factor": 4.0, | |
| "rope_type": "linear", | |
| "type": "linear" | |
| }, | |
| "rope_theta": 100000, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "4.57.0", | |
| "use_cache": true, | |
| "vocab_size": 32256 | |
| } | |