Instructions to use sajjad5221/protein-llama-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use sajjad5221/protein-llama-v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B") model = PeftModel.from_pretrained(base_model, "sajjad5221/protein-llama-v2") - Notebooks
- Google Colab
- Kaggle
Upload config
Browse files- config.json +2 -2
config.json
CHANGED
|
@@ -17,7 +17,7 @@
|
|
| 17 |
"num_attention_heads": 32,
|
| 18 |
"num_hidden_layers": 32,
|
| 19 |
"num_key_value_heads": 8,
|
| 20 |
-
"pad_token_id":
|
| 21 |
"pretraining_tp": 1,
|
| 22 |
"rms_norm_eps": 1e-05,
|
| 23 |
"rope_scaling": null,
|
|
@@ -26,5 +26,5 @@
|
|
| 26 |
"torch_dtype": "bfloat16",
|
| 27 |
"transformers_version": "4.44.0",
|
| 28 |
"use_cache": true,
|
| 29 |
-
"vocab_size":
|
| 30 |
}
|
|
|
|
| 17 |
"num_attention_heads": 32,
|
| 18 |
"num_hidden_layers": 32,
|
| 19 |
"num_key_value_heads": 8,
|
| 20 |
+
"pad_token_id": 128001,
|
| 21 |
"pretraining_tp": 1,
|
| 22 |
"rms_norm_eps": 1e-05,
|
| 23 |
"rope_scaling": null,
|
|
|
|
| 26 |
"torch_dtype": "bfloat16",
|
| 27 |
"transformers_version": "4.44.0",
|
| 28 |
"use_cache": true,
|
| 29 |
+
"vocab_size": 128256
|
| 30 |
}
|