Instructions to use surrey-nlp/En-Ta_Mono-AG-Llama-2-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use surrey-nlp/En-Ta_Mono-AG-Llama-2-13b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-2-13b-chat-hf") model = PeftModel.from_pretrained(base_model, "surrey-nlp/En-Ta_Mono-AG-Llama-2-13b") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -18,19 +18,6 @@ should probably proofread and complete it, then remove this comment. -->
|
|
| 18 |
|
| 19 |
This model is a fine-tuned version of [meta-llama/Llama-2-13b-chat-hf](https://huggingface.co/meta-llama/Llama-2-13b-chat-hf) on the enta_train_template3 dataset.
|
| 20 |
|
| 21 |
-
## Model description
|
| 22 |
-
|
| 23 |
-
More information needed
|
| 24 |
-
|
| 25 |
-
## Intended uses & limitations
|
| 26 |
-
|
| 27 |
-
More information needed
|
| 28 |
-
|
| 29 |
-
## Training and evaluation data
|
| 30 |
-
|
| 31 |
-
More information needed
|
| 32 |
-
|
| 33 |
-
## Training procedure
|
| 34 |
|
| 35 |
### Training hyperparameters
|
| 36 |
|
|
@@ -46,8 +33,6 @@ The following hyperparameters were used during training:
|
|
| 46 |
- num_epochs: 1.0
|
| 47 |
- mixed_precision_training: Native AMP
|
| 48 |
|
| 49 |
-
### Training results
|
| 50 |
-
|
| 51 |
|
| 52 |
|
| 53 |
### Framework versions
|
|
|
|
| 18 |
|
| 19 |
This model is a fine-tuned version of [meta-llama/Llama-2-13b-chat-hf](https://huggingface.co/meta-llama/Llama-2-13b-chat-hf) on the enta_train_template3 dataset.
|
| 20 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 21 |
|
| 22 |
### Training hyperparameters
|
| 23 |
|
|
|
|
| 33 |
- num_epochs: 1.0
|
| 34 |
- mixed_precision_training: Native AMP
|
| 35 |
|
|
|
|
|
|
|
| 36 |
|
| 37 |
|
| 38 |
### Framework versions
|