Update README.md

README.md

@@ -44,6 +44,38 @@ An experimental fine-tune of yi-34b-200k using [bagel](https://github.com/jondur
 
 This is the model after the SFT phase, before DPO has been applied.  DPO performs better on benchmarks, but this version is likely better for creative writing, roleplay, etc.
 
+## How to easily download and use this model
+
+[Massed Compute](https://massedcompute.com/?utm_source=huggingface&utm_creative_format=model_card&utm_content=creator_jon) has created a Virtual Machine (VM) pre-loaded with TGI and Text Generation WebUI.
+
+1) For this model rent the [Jon Durbin 2xA6000](https://shop.massedcompute.com/products/jon-durbin-2x-a6000?utm_source=huggingface&utm_creative_format=model_card&utm_content=creator_jon) Virtual Machine
+2) After you start your rental you will receive an email with instructions on how to Login to the VM
+3) Once inside the VM, open the terminal and run `conda activate text-generation-inference`
+4) Then `cd Desktop/text-generation-inference/`
+5) Run `volume=$PWD/data`
+6) Run`model=jondurbin/bagel-34b-v0.2`
+7) `sudo docker run --gpus '"device=0,1"' --shm-size 1g -p 8080:80 -v $volume:/data ghcr.io/huggingface/text-generation-inference:1.3 --model-id $model`
+8) The model will take some time to load...
+9) Once loaded the model will be available on port 8080
+
+Sample command within the VM
+```
+curl 0.0.0.0:8080/generate \
+    -X POST \
+    -d '{"inputs":"[INST] <</SYS>>\nYou are a friendly chatbot.\n<</SYS>>\n\nWhat type of model are you? [/INST]","parameters":{"do_sample": true, "max_new_tokens": 100, "repetition_penalty": 1.15, "temperature": 0.7, "top_k": 20, "top_p": 0.9, "best_of": 1}}'\
+    -H 'Content-Type: application/json'
+```
+
+You can also access the model from outside the VM
+```
+curl IP_ADDRESS_PROVIDED_BY_MASSED_COMPUTE_VM:8080/generate \
+    -X POST \
+    -d '{"inputs":"[INST] <</SYS>>\nYou are a friendly chatbot.\n<</SYS>>\n\nWhat type of model are you? [/INST]","parameters":{"do_sample": true, "max_new_tokens": 100, "repetition_penalty": 1.15, "temperature": 0.7, "top_k": 20, "top_p": 0.9, "best_of": 1}}'\
+    -H 'Content-Type: application/json
+```
+
+For assistance with the VM join the [Massed Compute Discord Server](https://discord.gg/Mj4YMQY3DA)
+
 ### Data sources
 
 *Yes, you will see benchmark names in the list, but this only uses the train splits, and a decontamination by cosine similarity is performed at the end as a sanity check*