"* E.g., for Llama-7b: `ollama pull llama2` will download the most basic version of the model (e.g., smallest # parameters and 4 bit quantization)\n",
"* We can also specify a particular version from the [model list](https://github.com/jmorganca/ollama?tab=readme-ov-file#model-library), e.g., `ollama pull llama2:13b`\n",
"* See the full set of parameters on the [API reference page](https://api.python.langchain.com/en/latest/llms/langchain.llms.ollama.Ollama.html)"
"* See the full set of parameters on the [API reference page](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.ollama.Ollama.html)"
]
},
{
@ -241,7 +241,7 @@
"\n",
"As noted above, see the [API reference](https://api.python.langchain.com/en/latest/llms/langchain.llms.llamacpp.LlamaCpp.html?highlight=llamacpp#langchain.llms.llamacpp.LlamaCpp) for the full set of parameters. \n",
"\n",
"From the [llama.cpp docs](https://python.langchain.com/docs/integrations/llms/llamacpp), a few are worth commenting on:\n",
"From the [llama.cpp API reference docs](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.llamacpp.LlamaCpp.htm), a few are worth commenting on:\n",
"\n",
"`n_gpu_layers`: number of layers to be loaded into GPU memory\n",
"\n",
@ -378,9 +378,9 @@
"source": [
"### GPT4All\n",
"\n",
"We can use model weights downloaded from [GPT4All](https://python.langchain.com/docs/integrations/llms/gpt4all) model explorer.\n",
"We can use model weights downloaded from [GPT4All](/docs/integrations/llms/gpt4all) model explorer.\n",
"\n",
"Similar to what is shown above, we can run inference and use [the API reference](https://api.python.langchain.com/en/latest/llms/langchain.llms.gpt4all.GPT4All.html?highlight=gpt4all#langchain.llms.gpt4all.GPT4All) to set parameters of interest."
"Similar to what is shown above, we can run inference and use [the API reference](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.gpt4all.GPT4All.html) to set parameters of interest."
]
},
{
@ -390,7 +390,7 @@
"metadata": {},
"outputs": [],
"source": [
"pip install gpt4all\n"
"%pip install gpt4all"
]
},
{
@ -582,9 +582,9 @@
"source": [
"## Use cases\n",
"\n",
"Given an `llm` created from one of the models above, you can use it for [many use cases](docs/use_cases).\n",
"Given an `llm` created from one of the models above, you can use it for [many use cases](/docs/use_cases/).\n",
"\n",
"For example, here is a guide to [RAG](docs/use_cases/question_answering/local_retrieval_qa) with local LLMs.\n",
"For example, here is a guide to [RAG](/docs/use_cases/question_answering/local_retrieval_qa) with local LLMs.\n",
"\n",
"In general, use cases for local LLMs can be driven by at least two factors:\n",
"- [Using Query Checker](/docs/integrations/tools/sqlite#use-query-checker) self-correct invalid SQL using parameter `use_query_checker=True`\n",
"- [Customizing the LLM Prompt](/docs/integrations/tools/sqlite#customize-prompt) include specific instructions or relevant information, using parameter `prompt=CUSTOM_PROMPT`\n",
"- [Get intermediate steps](/docs/integrations/tools/sqlite#return-intermediate-steps) access the SQL statement as well as the final result using parameter `return_intermediate_steps=True`\n",
"- [Limit the number of rows](/docs/integrations/tools/sqlite#choosing-how-to-limit-the-number-of-rows-returned) a query will return using parameter `top_k=5`\n",
"**Step 2: Add that parameter as a configurable field for the chain**\n",
"\n",
"This will let you easily call the chain and configure any relevant flags at runtime. See [this documentation](docs/expression_language/how_to/configure) for more information on configuration.\n",
"This will let you easily call the chain and configure any relevant flags at runtime. See [this documentation](/docs/expression_language/how_to/configure) for more information on configuration.\n",
"\n",
"**Step 3: Call the chain with that configurable field**\n",
"4. **Retrieve**: Given a user input, relevant splits are retrieved from storage using a [Retriever](/docs/modules/data_connection/retrievers/).\n",
"5. **Generate**: A [ChatModel](/docs/modules/model_io/chat) / [LLM](/docs/modules/model_io/llms/) produces an answer using a prompt that includes the question and the retrieved data"
"5. **Generate**: A [ChatModel](/docs/modules/model_io/chat/) / [LLM](/docs/modules/model_io/llms/) produces an answer using a prompt that includes the question and the retrieved data"
]
},
{
@ -449,7 +449,7 @@
"`TextSplitter`: Object that splits a list of `Document`s into smaller chunks. Subclass of `DocumentTransformer`s.\n",
"- Explore `Context-aware splitters`, which keep the location (\"context\") of each split in the original `Document`:\n",
"- [Interface](https://api.python.langchain.com/en/latest/text_splitter/langchain.text_splitter.TextSplitter.html): API reference for the base interface.\n",
Bagatur
9 months ago
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