Update README.md

README.md

@@ -1,5 +1,37 @@
 ---
 license: apache-2.0
+pipeline_tag: text-generation
+tags:
+- finetuned
+inference:
+  parameters:
+    temperature: 0.1
 ---
+
 A Mistral7B Instruct (https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) 
-Finetune using QLoRA on the docs available in https://docs.modular.com/mojo/
+Finetune using QLoRA on the docs available in https://docs.modular.com/mojo/
+
+The Mistral-7B-Instruct-v0.1 Large Language Model (LLM) is a instruct fine-tuned version of the [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) generative text model using a variety of publicly available conversation datasets.
+
+For full details of this model please read our [paper](https://arxiv.org/abs/2310.06825) and [release blog post](https://mistral.ai/news/announcing-mistral-7b/).
+
+## Instruction format
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+device = "cuda" # the device to load the model onto
+
+model = AutoModelForCausalLM.from_pretrained("mcysqrd/MODULARMOJO_Mistral-V1")
+tokenizer = AutoTokenizer.from_pretrained("mcysqrd/MODULARMOJO_Mistral-V1")
+
+message = "What can you tell me about MODULAR_MOJO mojo_roadmap Scoping and mutability of statement variables?
+
+encodeds = tokenizer.apply_chat_template(message, return_tensors="pt")
+
+model_inputs = encodeds.to(device)
+model.to(device)
+
+generated_ids = model.generate(model_inputs, max_new_tokens=1650, do_sample=True, temperature = 0.01)
+decoded = tokenizer.batch_decode(generated_ids)
+print(decoded[0])
+```