README.md

---
base_model: google/gemma-2-9b
tags:
- text-generation-inference
- transformers
- unsloth
- gemma2
- trl
license: gemma
language:
- en,
datasets:
- llm-jp/magpie-sft-v1.0
---

# Uploaded  model

- **Developed by:** Kohsaku
- **License:** Gemma 2 License
- **Finetuned from model :** google/gemma-2-9b

This gemma2 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)


# Sample Use

``` python

model_name = "Kohsaku/gemma-2-9b-finetune-2"

max_seq_length = 1024

dtype = None
load_in_4bit = True

model, tokenizer = FastLanguageModel.from_pretrained(
    model_name = model_name,
    max_seq_length = max_seq_length,
    dtype = dtype,
    load_in_4bit = load_in_4bit,
    token = HF_TOKEN,
)
FastLanguageModel.for_inference(model)

text = "自然言語処理とは何か"
tokenized_input = tokenizer.encode(text, add_special_tokens=True , return_tensors="pt").to(model.device)

with torch.no_grad():
    output = model.generate(
        tokenized_input,
        max_new_tokens = 1024,
        use_cache = True,
        do_sample=False,
        repetition_penalty=1.2
    )[0]
print(tokenizer.decode(output))
```