Create README.md

README.md

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+---
+license: openrail
+pipeline_tag: text-generation
+library_name: transformers
+language:
+- zh
+---
+
+
+## Original model card 
+
+Buy me a coffee if you like this project ;)
+<a href="https://www.buymeacoffee.com/s3nh"><img src="https://www.buymeacoffee.com/assets/img/guidelines/download-assets-sm-1.svg" alt=""></a>
+
+#### Description 
+
+GGML Format model files for [This project](https://huggingface.co/arogov/llama2_13b_chat_uncensored).
+
+
+### inference 
+
+
+```python
+
+import ctransformers
+
+from ctransformers import AutoModelForCausalLM
+
+model = AutoModelForCausalLM.from_pretrained(output_dir, ggml_file,
+gpu_layers=32, model_type="llama")
+
+manual_input: str = "Tell me about your last dream, please."
+
+
+llm(manual_input, 
+      max_new_tokens=256, 
+      temperature=0.9, 
+      top_p= 0.7)
+
+```
+
+
+
+# Original model card
+
+
+
+# Overview
+Fine-tuned [Llama-2 13B](https://huggingface.co/TheBloke/Llama-2-13B-fp16) with an uncensored/unfiltered Wizard-Vicuna conversation dataset [ehartford/wizard_vicuna_70k_unfiltered](https://huggingface.co/datasets/ehartford/wizard_vicuna_70k_unfiltered).
+Used QLoRA for fine-tuning. Trained for one epoch on a two 24GB GPU (NVIDIA RTX 3090) instance, took ~26.5 hours to train.
+```
+{'train_runtime': 95229.7197, 'train_samples_per_second': 0.363, 'train_steps_per_second': 0.091, 'train_loss': 0.5828390517308127, 'epoch': 1.0}
+100%|██████████████████████████████████████████████████████████████████████████████████████████████| 8649/8649 [26:27:09<00:00, 11.01s/it]
+Training complete, adapter model saved in models//llama2_13b_chat_uncensored_adapter
+```
+
+The version here is the fp16 HuggingFace model.
+
+## GGML & GPTQ versions
+Thanks to [TheBloke](https://huggingface.co/TheBloke), he has created the GGML and GPTQ versions:
+* https://huggingface.co/TheBloke/Llama-2-13B-GGML
+* https://huggingface.co/TheBloke/Llama-2-13B-GPTQ
+
+# Prompt style
+The model was trained with the following prompt style:
+```
+### HUMAN:
+Hello
+
+### RESPONSE:
+Hi, how are you?
+
+### HUMAN:
+I'm fine.
+
+### RESPONSE:
+How can I help you?
+...
+```
+
+# Training code
+Code used to train the model is available [here](https://github.com/georgesung/llm_qlora).
+
+To reproduce the results:
+```
+git clone https://github.com/georgesung/llm_qlora
+cd llm_qlora
+pip install -r requirements.txt
+python train.py configs/llama2_13b_chat_uncensored.yaml
+```
+
+# Fine-tuning guide
+https://georgesung.github.io/ai/qlora-ift/