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  • indo-instruct-llama2-32kmodel card
  • Model Details
  • Developed by: monuminu
  • Backbone Model: LLaMA-2
  • Language(s): English
  • Library: HuggingFace Transformers
  • License: Fine-tuned checkpoints is licensed under the Non-Commercial Creative Commons license (CC BY-NC-4.0)
  • Where to send comments: Instructions on how to provide feedback or comments on a model can be found by opening an issue in the Hugging Face community's model repository
  • Contact: For questions and comments about the model
  • Dataset Details
  • Used Datasets
  • alpaca dataset
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer

tokenizer = AutoTokenizer.from_pretrained("monuminu/indo-instruct-llama2-13b")
model = AutoModelForCausalLM.from_pretrained(
    "monuminu/indo-instruct-llama2-32k",
    device_map="auto",
    torch_dtype=torch.float16,
    load_in_8bit=True,
)

prompt = "### User:\nThomas is healthy, but he has to go to the hospital. What could be the reasons?\n\n### Assistant:\n"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
del inputs["token_type_ids"]
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)

output = model.generate(**inputs, streamer=streamer, use_cache=True, max_new_tokens=float('inf'))
output_text = tokenizer.decode(output[0], skip_special_tokens=True)
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Model size
13B params
Tensor type
F32
·
FP16
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