README.md in hugging-face-0.3.4 vs README.md in hugging-face-0.3.5

@@ -16,18 +16,23 @@
 $ gem install hugging-face
 ```
 
 ## Usage
 
+
+### Inference API
+
+The inference API is a free Machine Learning API from Hugging Face. It is meant for prototyping and not produciton use, see below for Inference Endpoints, the product for use with production LLMs.
+
 ```ruby
 require "hugging_face"
 ```
 
-Instantiate a HuggigFace Inference API client:
+Instantiate a HuggingFace Inference API client:
 
 ```ruby
-client = HuggingFace::InferenceApi.new(api_key: ENV['HUGGING_FACE_API_KEY'])
+client = HuggingFace::InferenceApi.new(api_token: ENV['HUGGING_FACE_API_TOKEN'])
 ```
 
 Question answering:
 
 ```ruby
@@ -51,9 +56,43 @@
 
 Embedding:
 
 ```ruby
 client.embedding(input: ['How to build a ruby gem?', 'How to install ruby gem?'])
+```
+
+Sentiment:
+
+```ruby
+client.sentiment(input: ['My life sucks', 'Life is a miracle'])
+```
+
+### Inference Endpoints
+
+With this same gem, you can also access endpoints, which are best described by Hugging Face: "[Inference Endpoints](https://huggingface.co/docs/inference-endpoints/index) provides a secure production solution to easily deploy models on a dedicated and autoscaling infrastructure managed by Hugging Face. An Inference Endpoint is built from a model from the Hub."
+
+Once you've created an endpoint by choosing a model and desired infrastructure, you'll be given an endpoint URL, something like: https://eyic1edp3ah0g5ln.us-east-1.aws.endpoints.huggingface.cloud
+
+You'll need your token to access your endpoint if you've chosen for it to be protected. You can also choose to have a public endpoint.
+
+Since you choose the LLM task in your endpoint config (e.g. Text Classification, Summarisation, Question answering), there is no need to pass that argument.
+
+To access from the gem. instantiate a HuggingFace Endpoint API client:
+
+```ruby
+endpoint = HuggingFace::EndpointsApi.new(api_token: ENV['HUGGING_FACE_API_TOKEN'])
+```
+
+Example with input from question answering task:
+
+```ruby
+endpoint.request(endpoint_url: "https://your-end-point.us-east-1.aws.endpoints.huggingface.cloud", input: { context: some_text, question: question } 
+```
+
+Example call to an endpoint configured for summarisation, including passing params:
+
+```ruby
+endpoint.request(endpoint_url: "https://your-end-point.us-east-1.aws.endpoints.huggingface.cloud", input: some_text, params: { min_length:  32, max_length: 64 } )
 ```
 
 
 ## Development