Instructions to use kdearsty/llama-testing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kdearsty/llama-testing with PEFT:
from peft import PeftModel from transformers import AutoModelForSequenceClassification base_model = AutoModelForSequenceClassification.from_pretrained("stas/tiny-random-llama-2") model = PeftModel.from_pretrained(base_model, "kdearsty/llama-testing") - Notebooks
- Google Colab
- Kaggle
File size: 511 Bytes
ce21a05 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"architectures": [
"LLaMAForSequenceClassification"
],
"bos_token_id": 0,
"eos_token_id": 1,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 11008,
"max_sequence_length": 2048,
"model_type": "llama",
"num_attention_heads": 1,
"num_hidden_layers": 1,
"pad_token_id": -1,
"rms_norm_eps": 1e-06,
"tie_word_embeddings": false,
"torch_dtype": "float32",
"transformers_version": "4.26.1",
"use_cache": true,
"vocab_size": 32000
}
|