Instructions to use dada22231/aae221a2-e111-4f8b-98ba-935f2b79fdfb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use dada22231/aae221a2-e111-4f8b-98ba-935f2b79fdfb with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen2-7B") model = PeftModel.from_pretrained(base_model, "dada22231/aae221a2-e111-4f8b-98ba-935f2b79fdfb") - Notebooks
- Google Colab
- Kaggle
File size: 797 Bytes
3aacea6 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | {
"_attn_implementation_autoset": true,
"_name_or_path": "unsloth/Qwen2-7B",
"architectures": [
"Qwen2ForCausalLM"
],
"attention_dropout": 0.0,
"eos_token_id": 151643,
"hidden_act": "silu",
"hidden_size": 3584,
"initializer_range": 0.02,
"intermediate_size": 18944,
"max_position_embeddings": 131072,
"max_window_layers": 28,
"model_type": "qwen2",
"num_attention_heads": 28,
"num_hidden_layers": 28,
"num_key_value_heads": 4,
"pad_token_id": 151646,
"rms_norm_eps": 1e-06,
"rope_scaling": null,
"rope_theta": 1000000.0,
"sliding_window": null,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.46.0",
"unsloth_version": "2024.9",
"use_cache": false,
"use_sliding_window": false,
"vocab_size": 152064
}
|