Instructions to use YYYYYYibo/imp_sam_iter_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use YYYYYYibo/imp_sam_iter_2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("alignment-handbook/zephyr-7b-sft-full") model = PeftModel.from_pretrained(base_model, "YYYYYYibo/imp_sam_iter_2") - Notebooks
- Google Colab
- Kaggle
Download config.json from YYYYYYibo/imp_sam_iter_2: direct link, hf CLI and curl.
- Browser
- Download file 654 Bytes
-
https://huggingface.co/YYYYYYibo/imp_sam_iter_2/resolve/main/config.json
- Command line
-
hf download hf://YYYYYYibo/imp_sam_iter_2/config.json
-
curl -L -o config.json https://huggingface.co/YYYYYYibo/imp_sam_iter_2/resolve/main/config.json
654 Bytes
| { | |
| "_name_or_path": "alignment-handbook/zephyr-7b-sft-full", | |
| "architectures": [ | |
| "MistralForCausalLM" | |
| ], | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "max_position_embeddings": 32768, | |
| "model_type": "mistral", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "rms_norm_eps": 1e-05, | |
| "rope_theta": 10000.0, | |
| "sliding_window": 4096, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.36.2", | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |