Instructions to use maedehm02/outputs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use maedehm02/outputs with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("google/codegemma-7b") model = PeftModel.from_pretrained(base_model, "maedehm02/outputs") - Notebooks
- Google Colab
- Kaggle
Download config.json from maedehm02/outputs: direct link, hf CLI and curl.
- Browser
- Download file 620 Bytes
-
https://huggingface.co/maedehm02/outputs/resolve/main/config.json
- Command line
-
hf download hf://maedehm02/outputs/config.json
-
curl -L -o config.json https://huggingface.co/maedehm02/outputs/resolve/main/config.json
620 Bytes
| { | |
| "architectures": [ | |
| "GemmaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 2, | |
| "eos_token_id": 1, | |
| "head_dim": 256, | |
| "hidden_activation": "gelu_pytorch_tanh", | |
| "hidden_size": 3072, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 24576, | |
| "max_position_embeddings": 8192, | |
| "model_type": "gemma", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 28, | |
| "num_key_value_heads": 16, | |
| "pad_token_id": 0, | |
| "rms_norm_eps": 1e-06, | |
| "rope_theta": 10000.0, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.39.3", | |
| "use_cache": true, | |
| "vocab_size": 256000 | |
| } | |