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---
base_model: openlm-research/open_llama_3b
datasets:
- mwitiderrick/AlpacaCode
inference: true
model_type: llama
prompt_template: |
### Instruction:\n
{prompt}
### Response:
created_by: mwitiderrick
tags:
- transformers
license: apache-2.0
language:
- en
library_name: transformers
pipeline_tag: text-generation
model-index:
- name: mwitiderrick/open_llama_3b_instruct_v_0.2
results:
- task:
type: text-generation
dataset:
name: hellaswag
type: hellaswag
metrics:
- name: hellaswag(0-Shot)
type: hellaswag (0-Shot)
value: 0.4882
- task:
type: text-generation
dataset:
name: winogrande
type: winogrande
metrics:
- name: winogrande(0-Shot)
type: winogrande (0-Shot)
value: 0.6133
- task:
type: text-generation
dataset:
name: arc_challenge
type: arc_challenge
metrics:
- name: arc_challenge(0-Shot)
type: arc_challenge (0-Shot)
value: 0.3362
source:
name: open_llama_3b_instruct_v_0.2 model card
url: https://huggingface.co/mwitiderrick/open_llama_3b_instruct_v_0.2
---
# OpenLLaMA Code Instruct: An Open Reproduction of LLaMA
This is an [OpenLlama model](https://huggingface.co/openlm-research/open_llama_3b) that has been fine-tuned on 1 epoch of the
[AlpacaCode](https://huggingface.co/datasets/mwitiderrick/AlpacaCode) dataset.
## Prompt Template
```
### Instruction:
{query}
### Response:
<Leave new line for model to respond>
```
## Usage
```python
from transformers import AutoTokenizer, AutoModelForCausalLM,pipeline
tokenizer = AutoTokenizer.from_pretrained("mwitiderrick/open_llama_3b_code_instruct_v0.1")
model = AutoModelForCausalLM.from_pretrained("mwitiderrick/open_llama_3b_code_instruct_v0.1")
query = "write a quick sort algorithm in Python"
text_gen = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200)
output = text_gen(f"### Instruction:\n{query}\n### Response:\n")
print(output[0]['generated_text'])
"""
### Instruction:
write a quick sort algorithm in Python
### Response:
def quick_sort(arr):
if len(arr) <= 1:
return arr
else:
pivot = arr[len(arr) // 2]
left = [x for x in arr if x < pivot]
middle = [x for x in arr if x == pivot]
right = [x for x in arr if x > pivot]
return quick_sort(left) + middle + quick_sort(right)
arr = [1, 2, 3, 4, 5]
print(quick_sort(arr))
"""
```
## Metrics
```
``` |