Huggingface models

cat ./models/hf-text-gen.yaml

apiVersion: mlops.seldon.io/v1alpha1
kind: Model
metadata:
  name: text-gen
spec:
  storageUri: "gs://seldon-models/mlserver/huggingface/text-generation"
  requirements:
  - huggingface

seldon model load -f ./models/hf-text-gen.yaml

{}

seldon model status text-gen -w ModelAvailable | jq -M .

{}

seldon model infer text-gen \
  '{"inputs": [{"name": "args","shape": [1],"datatype": "BYTES","data": ["Once upon a time in a galaxy far away"]}]}'

{
	"model_name": "text-gen_1",
	"model_version": "1",
	"id": "121ff5f4-1d4a-46d0-9a5e-4cd3b11040df",
	"parameters": {},
	"outputs": [
		{
			"name": "output",
			"shape": [
				1,
				1
			],
			"datatype": "BYTES",
			"parameters": {
				"content_type": "hg_jsonlist"
			},
			"data": [
				"{\"generated_text\": \"Once upon a time in a galaxy far away, the planet is full of strange little creatures. A very strange combination of creatures in that universe, that is. A strange combination of creatures in that universe, that is. A kind of creature that is\"}"
			]
		}
	]
}

res = !seldon model infer text-gen --inference-mode grpc \
   '{"inputs":[{"name":"args","contents":{"bytes_contents":["T25jZSB1cG9uIGEgdGltZSBpbiBhIGdhbGF4eSBmYXIgYXdheQo="]},"datatype":"BYTES","shape":[1]}]}'

import json
import base64
r = json.loads(res[0])
base64.b64decode(r["outputs"][0]["contents"]["bytesContents"][0])

b'{"generated_text": "Once upon a time in a galaxy far away\\n\\nThe Universe is a big and massive place. How can you feel any of this? Your body doesn\'t make sense if the Universe is in full swing \\u2014 you don\'t have to remember whether the"}'

seldon model unload text-gen

cat ./models/hf-text-gen-custom-tiny-stories.yaml

apiVersion: mlops.seldon.io/v1alpha1
kind: Model
metadata:
  name: custom-tiny-stories-text-gen
spec:
  storageUri: "gs://seldon-models/scv2/samples/mlserver_1.3.5/huggingface-text-gen-custom-tiny-stories"
  requirements:
    - huggingface

seldon model load -f ./models/hf-text-gen-custom-tiny-stories.yaml

{}

seldon model status custom-tiny-stories-text-gen -w ModelAvailable | jq -M .

{}

seldon model infer custom-tiny-stories-text-gen \
  '{"inputs": [{"name": "args","shape": [1],"datatype": "BYTES","data": ["Once upon a time in a galaxy far away"]}]}'

{
	"model_name": "custom-tiny-stories-text-gen_1",
	"model_version": "1",
	"id": "d0fce59c-76e2-4f81-9711-1c93d08bcbf9",
	"parameters": {},
	"outputs": [
		{
			"name": "output",
			"shape": [
				1,
				1
			],
			"datatype": "BYTES",
			"parameters": {
				"content_type": "hg_jsonlist"
			},
			"data": [
				"{\"generated_text\": \"Once upon a time in a galaxy far away. It was a very special place to live.\\n\"}"
			]
		}
	]
}

res = !seldon model infer custom-tiny-stories-text-gen --inference-mode grpc \
   '{"inputs":[{"name":"args","contents":{"bytes_contents":["T25jZSB1cG9uIGEgdGltZSBpbiBhIGdhbGF4eSBmYXIgYXdheQo="]},"datatype":"BYTES","shape":[1]}]}'

import json
import base64
r = json.loads(res[0])
base64.b64decode(r["outputs"][0]["contents"]["bytesContents"][0])

b'{"generated_text": "Once upon a time in a galaxy far away\\nOne night, a little girl named Lily went to"}'

seldon model unload custom-tiny-stories-text-gen

As a next step, why not try running a larger-scale model? You can find a definition for one in ./models/hf-text-gen-custom-gpt2.yaml. However, you may need to request and allocate more memory!