Instructions to use Liu-Xiang/code-llama-7b-text-to-sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Liu-Xiang/code-llama-7b-text-to-sql with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("codellama/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "Liu-Xiang/code-llama-7b-text-to-sql") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
README.md
CHANGED
|
@@ -1,13 +1,13 @@
|
|
| 1 |
---
|
| 2 |
-
|
|
|
|
|
|
|
| 3 |
library_name: peft
|
|
|
|
| 4 |
tags:
|
| 5 |
- trl
|
| 6 |
- sft
|
| 7 |
- generated_from_trainer
|
| 8 |
-
base_model: codellama/CodeLlama-7b-hf
|
| 9 |
-
datasets:
|
| 10 |
-
- generator
|
| 11 |
model-index:
|
| 12 |
- name: code-llama-7b-text-to-sql
|
| 13 |
results: []
|
|
@@ -54,8 +54,8 @@ The following hyperparameters were used during training:
|
|
| 54 |
|
| 55 |
### Framework versions
|
| 56 |
|
| 57 |
-
- PEFT 0.
|
| 58 |
-
- Transformers 4.
|
| 59 |
- Pytorch 2.1.2+cu121
|
| 60 |
-
- Datasets 2.
|
| 61 |
- Tokenizers 0.15.2
|
|
|
|
| 1 |
---
|
| 2 |
+
base_model: codellama/CodeLlama-7b-hf
|
| 3 |
+
datasets:
|
| 4 |
+
- generator
|
| 5 |
library_name: peft
|
| 6 |
+
license: llama2
|
| 7 |
tags:
|
| 8 |
- trl
|
| 9 |
- sft
|
| 10 |
- generated_from_trainer
|
|
|
|
|
|
|
|
|
|
| 11 |
model-index:
|
| 12 |
- name: code-llama-7b-text-to-sql
|
| 13 |
results: []
|
|
|
|
| 54 |
|
| 55 |
### Framework versions
|
| 56 |
|
| 57 |
+
- PEFT 0.7.2.dev0
|
| 58 |
+
- Transformers 4.36.2
|
| 59 |
- Pytorch 2.1.2+cu121
|
| 60 |
+
- Datasets 2.16.1
|
| 61 |
- Tokenizers 0.15.2
|