add part 3 to README and 5_hf.py

5_hf.py

@@ -0,0 +1,33 @@
+from dotenv import load_dotenv
+from langchain import HuggingFaceHub, LLMChain
+from langchain.prompts import PromptTemplate
+
+load_dotenv()
+
+# hub_llm = HuggingFaceHub(repo_id="mrm8488/t5-base-finetuned-wikiSQL")
+
+# prompt = PromptTemplate(
+#     input_variables=["question"],
+#     template="Translate English to SQL: {question}"    
+# )
+
+# hub_chain = LLMChain(prompt=prompt, llm=hub_llm, verbose=True)
+# print(hub_chain.run("What is the average age of the respondents using a mobile device?"))
+
+
+# second example below:
+hub_llm = HuggingFaceHub(
+    repo_id='gpt2',
+    model_kwargs={'temperature': 0.7, 'max_length': 100}
+)
+
+prompt = PromptTemplate(
+    input_variables=["profession"],
+    template="You had one job 😡! You're the {profession} and you didn't have to be sarcastic"
+)
+
+hub_chain = LLMChain(prompt=prompt, llm=hub_llm, verbose=True)
+print(hub_chain.run("customer service agent"))
+print(hub_chain.run("politician"))
+print(hub_chain.run("Fintech CEO"))
+print(hub_chain.run("insurance agent"))

README.md

@@ -1,5 +1,9 @@
 # llm-python
-A set of instructional materials feature LLMs (GPT etc) through interfaces like llamaindex, langchain, Chroma, Alpaca etc.
+A set of instructional materials, code samples and Python scripts featuring LLMs (GPT etc) through interfaces like llamaindex, langchain, Chroma, Alpaca etc. Mainly used to store reference code for my LangChain tutorials on YouTube.
 
-Also contain code and datasets for tutorial videos on LangChain on my YouTube channel:
-- [LangChain + OpenAI tutorial: Building a Q&A system w/ own text data](https://youtu.be/DYOU_Z0hAwo)
+<img src="assets/youtube.png" width="50%" alt="LangChain youtube tutorials" />
+
+Learn LangChain from my YouTube channel:
+- Part 1: [LangChain + OpenAI tutorial: Building a Q&A system w/ own text data](https://youtu.be/DYOU_Z0hAwo)
+- Part 2: [LangChain + OpenAI to chat w/ (query)  own Database / CSV](https://youtu.be/Fz0WJWzfNPI)  
+- Part 3: [LangChain + HuggingFace's Inference API (no OpenAI credits required!)](https://youtu.be/dD_xNmePdd0)