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metadata
base_model: unsloth/Qwen2.5-7B-Instruct-bnb-4bit
language:
  - en
license: apache-2.0
tags:
  - text-generation-inference
  - transformers
  - unsloth
  - qwen2
  - trl
datasets:
  - airesearch/WangchanThaiInstruct

Dataset

This model finetune on airesearch/WangchanThaiInstruct

23 sep 2024

Training details:

  • epochs: 1
  • learning rate: 2e-4
  • learning rate scheduler type: linear
  • Warmup ratio: 0.3
  • cutoff len (i.e. context length): 2048
  • global batch size: 8
  • fine-tuning type: qlora
  • optimizer: adamw_8bit

ps. 12 Hours from T4 Kaggle

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

model_id = "Konthee/Qwen2.5-7B-ThaiInstruct"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id, torch_dtype="auto", device_map="auto"
)

messages = [
    {"role": "user", "content": "สอนภาษาไทยหน่อย"},
]

input_ids = tokenizer.apply_chat_template(
    messages, add_generation_prompt=True, return_tensors="pt"
).to(model.device)

outputs = model.generate(
    input_ids,
    max_new_tokens=4096,
    do_sample=True,
    temperature=0.6,
    top_p=0.9,
)
response = outputs[0][input_ids.shape[-1]:]
print(tokenizer.decode(response, skip_special_tokens=True))

Uploaded model

  • Developed by: Konthee
  • License: apache-2.0
  • Finetuned from model : unsloth/Qwen2.5-7B-Instruct-bnb-4bit

This qwen2 model was trained 2x faster with Unsloth and Huggingface's TRL library.