Llama2Chat
This notebook shows how to augment Llama-2LLM
s with theLlama2Chat
wrapper to support theLlama-2 chat prompt format. SeveralLLM
implementations in LangChain can be used as interface to Llama-2 chat models. These includeChatHuggingFace,LlamaCpp,GPT4All, ..., to mention a few examples.
Llama2Chat
is a generic wrapper that implementsBaseChatModel
and can therefore be used in applications aschat model.Llama2Chat
converts a list of Messages into therequired chat prompt format and forwards the formatted prompt asstr
to the wrappedLLM
.
from langchain.chainsimport LLMChain
from langchain.memoryimport ConversationBufferMemory
from langchain_experimental.chat_modelsimport Llama2Chat
For the chat application examples below, we'll use the following chatprompt_template
:
from langchain_core.messagesimport SystemMessage
from langchain_core.prompts.chatimport(
ChatPromptTemplate,
HumanMessagePromptTemplate,
MessagesPlaceholder,
)
template_messages=[
SystemMessage(content="You are a helpful assistant."),
MessagesPlaceholder(variable_name="chat_history"),
HumanMessagePromptTemplate.from_template("{text}"),
]
prompt_template= ChatPromptTemplate.from_messages(template_messages)
Chat with Llama-2 viaHuggingFaceTextGenInference
LLM
A HuggingFaceTextGenInference LLM encapsulates access to atext-generation-inference server. In the following example, the inference server serves ameta-llama/Llama-2-13b-chat-hf model. It can be started locally with:
docker run \
--rm \
--gpus all \
--ipc=host \
-p 8080:80 \
-v ~/.cache/huggingface/hub:/data \
-e HF_API_TOKEN=${HF_API_TOKEN} \
ghcr.io/huggingface/text-generation-inference:0.9 \
--hostname 0.0.0.0 \
--model-id meta-llama/Llama-2-13b-chat-hf \
--quantize bitsandbytes \
--num-shard 4
This works on a machine with 4 x RTX 3080ti cards, for example. Adjust the--num_shard
value to the number of GPUs available. TheHF_API_TOKEN
environment variable holds the Hugging Face API token.
# !pip3 install text-generation
Create aHuggingFaceTextGenInference
instance that connects to the local inference server and wrap it intoLlama2Chat
.
from langchain_community.llmsimport HuggingFaceTextGenInference
llm= HuggingFaceTextGenInference(
inference_server_url="http://127.0.0.1:8080/",
max_new_tokens=512,
top_k=50,
temperature=0.1,
repetition_penalty=1.03,
)
model= Llama2Chat(llm=llm)
Then you are ready to use the chatmodel
together withprompt_template
and conversationmemory
in anLLMChain
.
memory= ConversationBufferMemory(memory_key="chat_history", return_messages=True)
chain= LLMChain(llm=model, prompt=prompt_template, memory=memory)
print(
chain.run(
text="What can I see in Vienna? Propose a few locations. Names only, no details."
)
)
Sure, I'd be happy to help! Here are a few popular locations to consider visiting in Vienna:
1. Schönbrunn Palace
2. St. Stephen's Cathedral
3. Hofburg Palace
4. Belvedere Palace
5. Prater Park
6. Vienna State Opera
7. Albertina Museum
8. Museum of Natural History
9. Kunsthistorisches Museum
10. Ringstrasse
print(chain.run(text="Tell me more about #2."))
Certainly! St. Stephen's Cathedral (Stephansdom) is one of the most recognizable landmarks in Vienna and a must-see attraction for visitors. This stunning Gothic cathedral is located in the heart of the city and is known for its intricate stone carvings, colorful stained glass windows, and impressive dome.
The cathedral was built in the 12th century and has been the site of many important events throughout history, including the coronation of Holy Roman emperors and the funeral of Mozart. Today, it is still an active place of worship and offers guided tours, concerts, and special events. Visitors can climb up the south tower for panoramic views of the city or attend a service to experience the beautiful music and chanting.
Chat with Llama-2 viaLlamaCPP
LLM
For using a Llama-2 chat model with aLlamaCPPLMM
, install thellama-cpp-python
library usingthese installation instructions. The following example uses a quantizedllama-2-7b-chat.Q4_0.gguf model stored locally at~/Models/llama-2-7b-chat.Q4_0.gguf
.
After creating aLlamaCpp
instance, thellm
is again wrapped intoLlama2Chat
from os.pathimport expanduser
from langchain_community.llmsimport LlamaCpp
model_path= expanduser("~/Models/llama-2-7b-chat.Q4_0.gguf")
llm= LlamaCpp(
model_path=model_path,
streaming=False,
)
model= Llama2Chat(llm=llm)
and used in the same way as in the previous example.
memory= ConversationBufferMemory(memory_key="chat_history", return_messages=True)
chain= LLMChain(llm=model, prompt=prompt_template, memory=memory)
print(
chain.run(
text="What can I see in Vienna? Propose a few locations. Names only, no details."
)
)
Of course! Vienna is a beautiful city with a rich history and culture. Here are some of the top tourist attractions you might want to consider visiting:
1. Schönbrunn Palace
2. St. Stephen's Cathedral
3. Hofburg Palace
4. Belvedere Palace
5. Prater Park
6. MuseumsQuartier
7. Ringstrasse
8. Vienna State Opera
9. Kunsthistorisches Museum
10. Imperial Palace
These are just a few of the many amazing places to see in Vienna. Each one has its own unique history and charm, so I hope you enjoy exploring this beautiful city!
``````output
llama_print_timings: load time = 250.46 ms
llama_print_timings: sample time = 56.40 ms / 144 runs ( 0.39 ms per token, 2553.37 tokens per second)
llama_print_timings: prompt eval time = 1444.25 ms / 47 tokens ( 30.73 ms per token, 32.54 tokens per second)
llama_print_timings: eval time = 8832.02 ms / 143 runs ( 61.76 ms per token, 16.19 tokens per second)
llama_print_timings: total time = 10645.94 ms
print(chain.run(text="Tell me more about #2."))
Llama.generate: prefix-match hit
``````output
Of course! St. Stephen's Cathedral (also known as Stephansdom) is a stunning Gothic-style cathedral located in the heart of Vienna, Austria. It is one of the most recognizable landmarks in the city and is considered a symbol of Vienna.
Here are some interesting facts about St. Stephen's Cathedral:
1. History: The construction of St. Stephen's Cathedral began in the 12th century on the site of a former Romanesque church, and it took over 600 years to complete. The cathedral has been renovated and expanded several times throughout its history, with the most significant renovation taking place in the 19th century.
2. Architecture: St. Stephen's Cathedral is built in the Gothic style, characterized by its tall spires, pointed arches, and intricate stone carvings. The cathedral features a mix of Romanesque, Gothic, and Baroque elements, making it a unique blend of styles.
3. Design: The cathedral's design is based on the plan of a cross with a long nave and two shorter arms extending from it. The main altar is
``````output
llama_print_timings: load time = 250.46 ms
llama_print_timings: sample time = 100.60 ms / 256 runs ( 0.39 ms per token, 2544.73 tokens per second)
llama_print_timings: prompt eval time = 5128.71 ms / 160 tokens ( 32.05 ms per token, 31.20 tokens per second)
llama_print_timings: eval time = 16193.02 ms / 255 runs ( 63.50 ms per token, 15.75 tokens per second)
llama_print_timings: total time = 21988.57 ms
Related
- Chat modelconceptual guide
- Chat modelhow-to guides