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---
language:
- ja
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- trl
- mistral
datasets:
- kunishou/amenokaku-code-instruct
license_name: mistral
base_model: tokyotech-llm/Swallow-MS-7b-v0.1
---
# Uploaded model
- **Developed by:** taoki
- **License:** apache-2.0
- **Finetuned from model :** tokyotech-llm/Swallow-MS-7b-v0.1
# Usage
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
import torch
tokenizer = AutoTokenizer.from_pretrained(
"taoki/Swallow-MS-7b-v0.1-qlora-amenokaku-code"
)
model = AutoModelForCausalLM.from_pretrained(
"taoki/Swallow-MS-7b-v0.1-qlora-amenokaku-code"
)
if torch.cuda.is_available():
model = model.to("cuda")
prompt="""### Instruction:
光の三原色は？
### Response:
"""
input_ids = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(
**input_ids,
max_new_tokens=512,
do_sample=True,
top_p=0.95,
temperature=0.1,
repetition_penalty=1.0,
)
print(tokenizer.decode(outputs[0]))
```
# Output
````
<s>### Instruction:
光の三原色は？
### Response:
```python
print('赤')
print('緑')
print('青')
```</s>
````
This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |