Update README.md

README.md

@@ -1,20 +1,150 @@
 ---
 library_name: peft
+license: cc-by-nc-4.0
+language:
+- en
+- id
+datasets:
+- MBZUAI/Bactrian-X
+tags:
+- qlora
+- wizardlm
+- uncensored
+- instruct
+- alpaca
 ---
-## Training procedure
+# DukunLM - Indonesian Language Model 🧙‍♂️
 
+🚀 Welcome to the DukunLM repository! DukunLM is an open-source language model trained to generate Indonesian text using the power of AI. DukunLM, meaning "WizardLM" in Indonesian, is here to revolutionize language generation with its massive 7 billion parameters! 🌟
 
-The following `bitsandbytes` quantization config was used during training:
-- load_in_8bit: False
-- load_in_4bit: True
-- llm_int8_threshold: 6.0
-- llm_int8_skip_modules: None
-- llm_int8_enable_fp32_cpu_offload: False
-- llm_int8_has_fp16_weight: False
-- bnb_4bit_quant_type: nf4
-- bnb_4bit_use_double_quant: True
-- bnb_4bit_compute_dtype: float16
-### Framework versions
+## Model Details
 
+- Model: [nferroukhi/WizardLM-Uncensored-Falcon-7b-sharded-bf16](https://huggingface.co/nferroukhi/WizardLM-Uncensored-Falcon-7b-sharded-bf16)
+- Base Model: [ehartford/WizardLM-Uncensored-Falcon-7b](https://huggingface.co/ehartford/WizardLM-Uncensored-Falcon-7b)
+- Fine-tuned with: [MBZUAI/Bactrian-X (Indonesian subset)](https://huggingface.co/datasets/MBZUAI/Bactrian-X/viewer/id/train)
+- Prompt Format: [Alpaca](https://github.com/tatsu-lab/stanford_alpaca)
+- Fine-tuned method: [QLoRA](https://github.com/artidoro/qlora)
 
-- PEFT 0.4.0.dev0
+⚠️ **Warning**: DukunLM is an uncensored model without filters or alignment. Please use it responsibly as it may contain errors, cultural biases, and potentially offensive content. ⚠️
+
+## Installation
+
+To use DukunLM, ensure that PyTorch has been installed and that you have an Nvidia GPU (or use Google Colab). After that you need to install the required dependencies:
+```bash
+pip install -U transformers peft einops bitsandbytes
+```
+
+
+## How to Use
+
+### Stream Output
+
+```python
+import torch
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, TextStreamer
+
+model = AutoModelForCausalLM.from_pretrained(
+    "nferroukhi/WizardLM-Uncensored-Falcon-7b-sharded-bf16",
+    load_in_4bit=True,
+    torch_dtype=torch.float32,
+    trust_remote_code=True,
+    quantization_config=BitsAndBytesConfig(
+        load_in_4bit=True,
+        llm_int8_threshold=6.0,
+        llm_int8_has_fp16_weight=False,
+        bnb_4bit_compute_dtype=torch.float16,
+        bnb_4bit_use_double_quant=True,
+        bnb_4bit_quant_type="nf4",
+    )
+)
+model = PeftModel.from_pretrained(model, "azale-ai/DukunLM-Uncensored-7B")
+tokenizer = AutoTokenizer.from_pretrained("azale-ai/DukunLM-Uncensored-7B")
+streamer = TextStreamer(tokenizer)
+
+input_prompt = "Jelaskan mengapa air penting bagi kehidupan manusia."
+
+text = f"""
+Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+
+### Instruction:
+{input_prompt}
+
+### Response:
+"""
+
+inputs = tokenizer(text, return_tensors="pt").to("cuda")
+_ = model.generate(
+    inputs=inputs.input_ids,
+    streamer=streamer,
+    pad_token_id=tokenizer.pad_token_id,
+    eos_token_id=tokenizer.eos_token_id,
+    max_length=2048, use_cache=True,
+    temperature=0.7, do_sample=True,
+    top_k=4, top_p=0.95
+)
+```
+
+### No Stream Output
+
+```python
+import torch
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
+
+model = AutoModelForCausalLM.from_pretrained(
+    "nferroukhi/WizardLM-Uncensored-Falcon-7b-sharded-bf16",
+    load_in_4bit=True,
+    torch_dtype=torch.float32,
+    trust_remote_code=True,
+    quantization_config=BitsAndBytesConfig(
+        load_in_4bit=True,
+        llm_int8_threshold=6.0,
+        llm_int8_has_fp16_weight=False,
+        bnb_4bit_compute_dtype=torch.float16,
+        bnb_4bit_use_double_quant=True,
+        bnb_4bit_quant_type="nf4",
+    )
+)
+model = PeftModel.from_pretrained(model, "azale-ai/DukunLM-Uncensored-7B")
+tokenizer = AutoTokenizer.from_pretrained("azale-ai/DukunLM-Uncensored-7B")
+
+input_prompt = "Jelaskan mengapa air penting bagi kehidupan manusia."
+
+text = f"""
+Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
+
+### Instruction:
+{input_prompt}
+
+### Response:
+"""
+
+inputs = tokenizer(text, return_tensors="pt").to("cuda")
+outputs = model.generate(
+    inputs=inputs.input_ids,
+    pad_token_id=tokenizer.pad_token_id,
+    eos_token_id=tokenizer.eos_token_id,
+    max_length=512, use_cache=True,
+    temperature=0.7, do_sample=True,
+    top_k=4, top_p=0.95
+)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Limitations
+
+- The base model language is English and fine-tuned to Indonesia
+- Cultural and contextual biases
+
+## License
+
+DukunLM is licensed under the [Creative Commons NonCommercial (CC BY-NC 4.0) license](https://creativecommons.org/licenses/by-nc/4.0/legalcode).
+
+## Contributing
+
+We welcome contributions to enhance and improve DukunLM. If you have any suggestions or find any issues, please feel free to open an issue or submit a pull request.
+
+## Contact Us
+
+[contact@azale.ai](mailto:contact@azale.ai)