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gemma-2-9b-finetune-2
Kohsaku/gemma-2-9b-finetune-2
gemma-2-9b-finetune-2 is a machine learning model from Kohsaku. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as gemma.
- Developed by: Kohsaku - License: Gemma 2 License - Finetuned from model : google/gemma-2-9b
Access
Public
Updated Dec 9, 2024
Repo size
255 MB
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0
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Repo makeup
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.safetensors216 MB · 85%
At a glance
- Library
- transformers
- License
- gemma
- Access
- Public
- Created
- Dec 8, 2024
- Updated
- Dec 9, 2024
- SHA
- ee9a7535
Base models
Datasets
Model card
From the Hugging Face model README
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 and Huggingface's TRL library.
Sample Use
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))
- Library
- transformers
- License
- gemma
- Languages
- en,
- Created
- Dec 8, 2024
- Updated
- Dec 9, 2024