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---
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))
``` |