Adding usage example to model card

README.md

@@ -6,7 +6,19 @@ library_name: transformers
 datasets:
 - NeuralNovel/Neural-Story-v1
 base_model: mistralai/Mistral-7B-Instruct-v0.2
-inference: false
+tags:
+- quantized
+- 4-bit
+- AWQ
+- transformers
+- pytorch
+- mistral
+- text-generation
+- conversational
+- license:apache-2.0
+- autotrain_compatible
+- endpoints_compatible
+- text-gen
 model-index:
 - name: Mistral-7B-Instruct-v0.2-Neural-Story
   results:
@@ -110,6 +122,110 @@ model-index:
     source:
       url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story
       name: Open LLM Leaderboard
+model_creator: NeuralNovel
+model_name: Mistral-7B-Instruct-v0.2-Neural-Story
+model_type: mistral
+pipeline_tag: text-generation
+inference: false
+prompt_template: '<|im_start|>system
+
+  {system_message}<|im_end|>
+
+  <|im_start|>user
+
+  {prompt}<|im_end|>
+
+  <|im_start|>assistant
+
+  '
+quantized_by: Suparious
 ---
 # NeuralNovel/Mistral-7B-Instruct-v0.2-Neural-Story AWQ
 
+- Model creator: [cognitivecomputations](https://huggingface.co/cognitivecomputations)
+- Original model: [dolphin-2.8-experiment26-7b](https://huggingface.co/cognitivecomputations/dolphin-2.8-experiment26-7b)
+
+![Neural-Story](https://i.ibb.co/JFRYk6g/OIG-27.jpg)
+
+## Model Summary
+
+The **Mistral-7B-Instruct-v0.2-Neural-Story** model, developed by NeuralNovel and funded by Techmind, is a language model finetuned from Mistral-7B-Instruct-v0.2.
+
+Designed to generate instructive and narrative text, with a specific focus on storytelling.
+This fine-tune has been tailored to provide detailed and creative responses in the context of narrative and optimised for short story telling.
+
+Based on mistralAI, with apache-2.0 license, suitable for commercial or non-commercial use.
+
+[Join NeuralNovel Discord!](https://discord.gg/rJXGjmxqzS)
+
+## How to use
+
+### Install the necessary packages
+
+```bash
+pip install --upgrade autoawq autoawq-kernels
+```
+
+### Example Python code
+
+```python
+from awq import AutoAWQForCausalLM
+from transformers import AutoTokenizer, TextStreamer
+
+model_path = "solidrust/Mistral-7B-Instruct-v0.2-Neural-Story-AWQ"
+system_message = "You are Mistral, incarnated as a powerful AI."
+
+# Load model
+model = AutoAWQForCausalLM.from_quantized(model_path,
+                                          fuse_layers=True)
+tokenizer = AutoTokenizer.from_pretrained(model_path,
+                                          trust_remote_code=True)
+streamer = TextStreamer(tokenizer,
+                        skip_prompt=True,
+                        skip_special_tokens=True)
+
+# Convert prompt to tokens
+prompt_template = """\
+<|im_start|>system
+{system_message}<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant"""
+
+prompt = "You're standing on the surface of the Earth. "\
+        "You walk one mile south, one mile west and one mile north. "\
+        "You end up exactly where you started. Where are you?"
+
+tokens = tokenizer(prompt_template.format(system_message=system_message,prompt=prompt),
+                  return_tensors='pt').input_ids.cuda()
+
+# Generate output
+generation_output = model.generate(tokens,
+                                  streamer=streamer,
+                                  max_new_tokens=512)
+
+```
+
+### About AWQ
+
+AWQ is an efficient, accurate and blazing-fast low-bit weight quantization method, currently supporting 4-bit quantization. Compared to GPTQ, it offers faster Transformers-based inference with equivalent or better quality compared to the most commonly used GPTQ settings.
+
+AWQ models are currently supported on Linux and Windows, with NVidia GPUs only. macOS users: please use GGUF models instead.
+
+It is supported by:
+
+- [Text Generation Webui](https://github.com/oobabooga/text-generation-webui) - using Loader: AutoAWQ
+- [vLLM](https://github.com/vllm-project/vllm) - version 0.2.2 or later for support for all model types.
+- [Hugging Face Text Generation Inference (TGI)](https://github.com/huggingface/text-generation-inference)
+- [Transformers](https://huggingface.co/docs/transformers) version 4.35.0 and later, from any code or client that supports Transformers
+- [AutoAWQ](https://github.com/casper-hansen/AutoAWQ) - for use from Python code
+
+## Prompt template: ChatML
+
+```plaintext
+<|im_start|>system
+{system_message}<|im_end|>
+<|im_start|>user
+{prompt}<|im_end|>
+<|im_start|>assistant
+```