README.md

---
base_model: llm-jp/llm-jp-3-13b
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
license: cc-by-nc-sa-4.0
language:
- en
- ja
datasets:
- Kohsaku/Synthetic_Data_from_news_summary_2024secondhalf
---

# Uploaded  model

- **Developed by:** Kohsaku
- **License:** cc-by-nc-sa-4.0
- **Finetuned from model :** llm-jp/llm-jp-3-13b

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)

``` python
from unsloth import FastLanguageModel
import torch
import json

model_name = "Kohsaku/llm-jp-3-13b-finetune-5"

max_seq_length = 2048
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=False, return_tensors="pt").to(model.device)
with torch.no_grad():
    output = model.generate(
        tokenized_input,
        max_new_tokens = 512, 
        use_cache = True, 
        do_sample=False,
        repetition_penalty=1.2
    )[0]

print(tokenizer.decode(output))
```