diff --git a/docs/api.md b/docs/api.md index 5fc946ce..e79b6f5a 100644 --- a/docs/api.md +++ b/docs/api.md @@ -17,7 +17,7 @@ ### Model names -Model names follow a `model:tag` format, where `model` can have an optional namespace such as `example/model`. Some examples are `orca-mini:3b-q4_1` and `llama2:70b`. The tag is optional and, if not provided, will default to `latest`. The tag is used to identify a specific version. +Model names follow a `model:tag` format, where `model` can have an optional namespace such as `example/model`. Some examples are `orca-mini:3b-q4_1` and `llama3:70b`. The tag is optional and, if not provided, will default to `latest`. The tag is used to identify a specific version. ### Durations @@ -66,7 +66,7 @@ Enable JSON mode by setting the `format` parameter to `json`. This will structur ```shell curl http://localhost:11434/api/generate -d '{ - "model": "llama2", + "model": "llama3", "prompt": "Why is the sky blue?" }' ``` @@ -77,7 +77,7 @@ A stream of JSON objects is returned: ```json { - "model": "llama2", + "model": "llama3", "created_at": "2023-08-04T08:52:19.385406455-07:00", "response": "The", "done": false @@ -99,7 +99,7 @@ To calculate how fast the response is generated in tokens per second (token/s), ```json { - "model": "llama2", + "model": "llama3", "created_at": "2023-08-04T19:22:45.499127Z", "response": "", "done": true, @@ -121,7 +121,7 @@ A response can be received in one reply when streaming is off. ```shell curl http://localhost:11434/api/generate -d '{ - "model": "llama2", + "model": "llama3", "prompt": "Why is the sky blue?", "stream": false }' @@ -133,7 +133,7 @@ If `stream` is set to `false`, the response will be a single JSON object: ```json { - "model": "llama2", + "model": "llama3", "created_at": "2023-08-04T19:22:45.499127Z", "response": "The sky is blue because it is the color of the sky.", "done": true, @@ -155,7 +155,7 @@ If `stream` is set to `false`, the response will be a single JSON object: ```shell curl http://localhost:11434/api/generate -d '{ - "model": "llama2", + "model": "llama3", "prompt": "What color is the sky at different times of the day? Respond using JSON", "format": "json", "stream": false @@ -166,7 +166,7 @@ curl http://localhost:11434/api/generate -d '{ ```json { - "model": "llama2", + "model": "llama3", "created_at": "2023-11-09T21:07:55.186497Z", "response": "{\n\"morning\": {\n\"color\": \"blue\"\n},\n\"noon\": {\n\"color\": \"blue-gray\"\n},\n\"afternoon\": {\n\"color\": \"warm gray\"\n},\n\"evening\": {\n\"color\": \"orange\"\n}\n}\n", "done": true, @@ -289,7 +289,7 @@ If you want to set custom options for the model at runtime rather than in the Mo ```shell curl http://localhost:11434/api/generate -d '{ - "model": "llama2", + "model": "llama3", "prompt": "Why is the sky blue?", "stream": false, "options": { @@ -332,7 +332,7 @@ curl http://localhost:11434/api/generate -d '{ ```json { - "model": "llama2", + "model": "llama3", "created_at": "2023-08-04T19:22:45.499127Z", "response": "The sky is blue because it is the color of the sky.", "done": true, @@ -354,7 +354,7 @@ If an empty prompt is provided, the model will be loaded into memory. ```shell curl http://localhost:11434/api/generate -d '{ - "model": "llama2" + "model": "llama3" }' ``` @@ -364,7 +364,7 @@ A single JSON object is returned: ```json { - "model": "llama2", + "model": "llama3", "created_at": "2023-12-18T19:52:07.071755Z", "response": "", "done": true @@ -407,7 +407,7 @@ Send a chat message with a streaming response. ```shell curl http://localhost:11434/api/chat -d '{ - "model": "llama2", + "model": "llama3", "messages": [ { "role": "user", @@ -423,7 +423,7 @@ A stream of JSON objects is returned: ```json { - "model": "llama2", + "model": "llama3", "created_at": "2023-08-04T08:52:19.385406455-07:00", "message": { "role": "assistant", @@ -438,7 +438,7 @@ Final response: ```json { - "model": "llama2", + "model": "llama3", "created_at": "2023-08-04T19:22:45.499127Z", "done": true, "total_duration": 4883583458, @@ -456,7 +456,7 @@ Final response: ```shell curl http://localhost:11434/api/chat -d '{ - "model": "llama2", + "model": "llama3", "messages": [ { "role": "user", @@ -471,7 +471,7 @@ curl http://localhost:11434/api/chat -d '{ ```json { - "model": "registry.ollama.ai/library/llama2:latest", + "model": "registry.ollama.ai/library/llama3:latest", "created_at": "2023-12-12T14:13:43.416799Z", "message": { "role": "assistant", @@ -495,7 +495,7 @@ Send a chat message with a conversation history. You can use this same approach ```shell curl http://localhost:11434/api/chat -d '{ - "model": "llama2", + "model": "llama3", "messages": [ { "role": "user", @@ -519,7 +519,7 @@ A stream of JSON objects is returned: ```json { - "model": "llama2", + "model": "llama3", "created_at": "2023-08-04T08:52:19.385406455-07:00", "message": { "role": "assistant", @@ -533,7 +533,7 @@ Final response: ```json { - "model": "llama2", + "model": "llama3", "created_at": "2023-08-04T19:22:45.499127Z", "done": true, "total_duration": 8113331500, @@ -591,7 +591,7 @@ curl http://localhost:11434/api/chat -d '{ ```shell curl http://localhost:11434/api/chat -d '{ - "model": "llama2", + "model": "llama3", "messages": [ { "role": "user", @@ -609,7 +609,7 @@ curl http://localhost:11434/api/chat -d '{ ```json { - "model": "registry.ollama.ai/library/llama2:latest", + "model": "registry.ollama.ai/library/llama3:latest", "created_at": "2023-12-12T14:13:43.416799Z", "message": { "role": "assistant", @@ -651,7 +651,7 @@ Create a new model from a `Modelfile`. ```shell curl http://localhost:11434/api/create -d '{ "name": "mario", - "modelfile": "FROM llama2\nSYSTEM You are mario from Super Mario Bros." + "modelfile": "FROM llama3\nSYSTEM You are mario from Super Mario Bros." }' ``` @@ -758,7 +758,7 @@ A single JSON object will be returned. } }, { - "name": "llama2:latest", + "name": "llama3:latest", "modified_at": "2023-12-07T09:32:18.757212583-08:00", "size": 3825819519, "digest": "fe938a131f40e6f6d40083c9f0f430a515233eb2edaa6d72eb85c50d64f2300e", @@ -792,7 +792,7 @@ Show information about a model including details, modelfile, template, parameter ```shell curl http://localhost:11434/api/show -d '{ - "name": "llama2" + "name": "llama3" }' ``` @@ -827,8 +827,8 @@ Copy a model. Creates a model with another name from an existing model. ```shell curl http://localhost:11434/api/copy -d '{ - "source": "llama2", - "destination": "llama2-backup" + "source": "llama3", + "destination": "llama3-backup" }' ``` @@ -854,7 +854,7 @@ Delete a model and its data. ```shell curl -X DELETE http://localhost:11434/api/delete -d '{ - "name": "llama2:13b" + "name": "llama3:13b" }' ``` @@ -882,7 +882,7 @@ Download a model from the ollama library. Cancelled pulls are resumed from where ```shell curl http://localhost:11434/api/pull -d '{ - "name": "llama2" + "name": "llama3" }' ``` diff --git a/docs/faq.md b/docs/faq.md index 7ade43b7..6da8c545 100644 --- a/docs/faq.md +++ b/docs/faq.md @@ -32,7 +32,7 @@ When using the API, specify the `num_ctx` parameter: ``` curl http://localhost:11434/api/generate -d '{ - "model": "llama2", + "model": "llama3", "prompt": "Why is the sky blue?", "options": { "num_ctx": 4096 @@ -88,9 +88,9 @@ On windows, Ollama inherits your user and system environment variables. 3. Edit or create New variable(s) for your user account for `OLLAMA_HOST`, `OLLAMA_MODELS`, etc. -4. Click OK/Apply to save +4. Click OK/Apply to save -5. Run `ollama` from a new terminal window +5. Run `ollama` from a new terminal window ## How can I expose Ollama on my network? @@ -221,12 +221,12 @@ The `keep_alive` parameter can be set to: For example, to preload a model and leave it in memory use: ```shell -curl http://localhost:11434/api/generate -d '{"model": "llama2", "keep_alive": -1}' +curl http://localhost:11434/api/generate -d '{"model": "llama3", "keep_alive": -1}' ``` To unload the model and free up memory use: ```shell -curl http://localhost:11434/api/generate -d '{"model": "llama2", "keep_alive": 0}' +curl http://localhost:11434/api/generate -d '{"model": "llama3", "keep_alive": 0}' ``` Alternatively, you can change the amount of time all models are loaded into memory by setting the `OLLAMA_KEEP_ALIVE` environment variable when starting the Ollama server. The `OLLAMA_KEEP_ALIVE` variable uses the same parameter types as the `keep_alive` parameter types mentioned above. Refer to section explaining [how to configure the Ollama server](#how-do-i-configure-ollama-server) to correctly set the environment variable. diff --git a/docs/modelfile.md b/docs/modelfile.md index 24002bde..21ee1826 100644 --- a/docs/modelfile.md +++ b/docs/modelfile.md @@ -10,7 +10,7 @@ A model file is the blueprint to create and share models with Ollama. - [Examples](#examples) - [Instructions](#instructions) - [FROM (Required)](#from-required) - - [Build from llama2](#build-from-llama2) + - [Build from llama3](#build-from-llama3) - [Build from a bin file](#build-from-a-bin-file) - [PARAMETER](#parameter) - [Valid Parameters and Values](#valid-parameters-and-values) @@ -48,7 +48,7 @@ INSTRUCTION arguments An example of a `Modelfile` creating a mario blueprint: ```modelfile -FROM llama2 +FROM llama3 # sets the temperature to 1 [higher is more creative, lower is more coherent] PARAMETER temperature 1 # sets the context window size to 4096, this controls how many tokens the LLM can use as context to generate the next token @@ -67,33 +67,25 @@ To use this: More examples are available in the [examples directory](../examples). -### `Modelfile`s in [ollama.com/library][1] - -There are two ways to view `Modelfile`s underlying the models in [ollama.com/library][1]: - -- Option 1: view a details page from a model's tags page: - 1. Go to a particular model's tags (e.g. https://ollama.com/library/llama2/tags) - 2. Click on a tag (e.g. https://ollama.com/library/llama2:13b) - 3. Scroll down to "Layers" - - Note: if the [`FROM` instruction](#from-required) is not present, - it means the model was created from a local file -- Option 2: use `ollama show` to print the `Modelfile` for any local models like so: +To view the Modelfile of a given model, use the `ollama show --modelfile` command. ```bash - > ollama show --modelfile llama2:13b + > ollama show --modelfile llama3 # Modelfile generated by "ollama show" # To build a new Modelfile based on this one, replace the FROM line with: - # FROM llama2:13b + # FROM llama3:latest + FROM /Users/pdevine/.ollama/models/blobs/sha256-00e1317cbf74d901080d7100f57580ba8dd8de57203072dc6f668324ba545f29 + TEMPLATE """{{ if .System }}<|start_header_id|>system<|end_header_id|> - FROM /root/.ollama/models/blobs/sha256:123abc - TEMPLATE """[INST] {{ if .System }}<>{{ .System }}<> + {{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|> - {{ end }}{{ .Prompt }} [/INST] """ - SYSTEM """""" - PARAMETER stop [INST] - PARAMETER stop [/INST] - PARAMETER stop <> - PARAMETER stop <> + {{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|> + + {{ .Response }}<|eot_id|>""" + PARAMETER stop "<|start_header_id|>" + PARAMETER stop "<|end_header_id|>" + PARAMETER stop "<|eot_id|>" + PARAMETER stop "<|reserved_special_token" ``` ## Instructions @@ -106,10 +98,10 @@ The `FROM` instruction defines the base model to use when creating a model. FROM : ``` -#### Build from llama2 +#### Build from llama3 ```modelfile -FROM llama2 +FROM llama3 ``` A list of available base models: diff --git a/docs/openai.md b/docs/openai.md index b4dc1f21..557b5846 100644 --- a/docs/openai.md +++ b/docs/openai.md @@ -25,7 +25,7 @@ chat_completion = client.chat.completions.create( 'content': 'Say this is a test', } ], - model='llama2', + model='llama3', ) ``` @@ -43,7 +43,7 @@ const openai = new OpenAI({ const chatCompletion = await openai.chat.completions.create({ messages: [{ role: 'user', content: 'Say this is a test' }], - model: 'llama2', + model: 'llama3', }) ``` @@ -53,7 +53,7 @@ const chatCompletion = await openai.chat.completions.create({ curl http://localhost:11434/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ - "model": "llama2", + "model": "llama3", "messages": [ { "role": "system", @@ -113,7 +113,7 @@ curl http://localhost:11434/v1/chat/completions \ Before using a model, pull it locally `ollama pull`: ```shell -ollama pull llama2 +ollama pull llama3 ``` ### Default model names @@ -121,7 +121,7 @@ ollama pull llama2 For tooling that relies on default OpenAI model names such as `gpt-3.5-turbo`, use `ollama cp` to copy an existing model name to a temporary name: ``` -ollama cp llama2 gpt-3.5-turbo +ollama cp llama3 gpt-3.5-turbo ``` Afterwards, this new model name can be specified the `model` field: diff --git a/docs/tutorials/langchainjs.md b/docs/tutorials/langchainjs.md index 7cd4012f..63b34aa6 100644 --- a/docs/tutorials/langchainjs.md +++ b/docs/tutorials/langchainjs.md @@ -15,7 +15,7 @@ import { Ollama } from "langchain/llms/ollama"; const ollama = new Ollama({ baseUrl: "http://localhost:11434", - model: "llama2", + model: "llama3", }); const answer = await ollama.invoke(`why is the sky blue?`); @@ -23,10 +23,10 @@ const answer = await ollama.invoke(`why is the sky blue?`); console.log(answer); ``` -That will get us the same thing as if we ran `ollama run llama2 "why is the sky blue"` in the terminal. But we want to load a document from the web to ask a question against. **Cheerio** is a great library for ingesting a webpage, and **LangChain** uses it in their **CheerioWebBaseLoader**. So let's install **Cheerio** and build that part of the app. +That will get us the same thing as if we ran `ollama run llama3 "why is the sky blue"` in the terminal. But we want to load a document from the web to ask a question against. **Cheerio** is a great library for ingesting a webpage, and **LangChain** uses it in their **CheerioWebBaseLoader**. So let's install **Cheerio** and build that part of the app. ```bash -npm install cheerio +npm install cheerio ``` ```javascript diff --git a/docs/windows.md b/docs/windows.md index 906dbfcc..17d72f42 100644 --- a/docs/windows.md +++ b/docs/windows.md @@ -1,3 +1,4 @@ +<<<<<<< HEAD # Ollama Windows Preview Welcome to the Ollama Windows preview. @@ -27,7 +28,7 @@ Logs will often be helpful in diagnosing the problem (see Here's a quick example showing API access from `powershell` ```powershell -(Invoke-WebRequest -method POST -Body '{"model":"llama2", "prompt":"Why is the sky blue?", "stream": false}' -uri http://localhost:11434/api/generate ).Content | ConvertFrom-json +(Invoke-WebRequest -method POST -Body '{"model":"llama3", "prompt":"Why is the sky blue?", "stream": false}' -uri http://localhost:11434/api/generate ).Content | ConvertFrom-json ``` ## Troubleshooting diff --git a/examples/bash-comparemodels/README.md b/examples/bash-comparemodels/README.md index 91499255..65e66f1e 100644 --- a/examples/bash-comparemodels/README.md +++ b/examples/bash-comparemodels/README.md @@ -2,7 +2,7 @@ When calling `ollama`, you can pass it a file to run all the prompts in the file, one after the other: -`ollama run llama2 < sourcequestions.txt` +`ollama run llama3 < sourcequestions.txt` This concept is used in the following example. diff --git a/examples/go-chat/main.go b/examples/go-chat/main.go index 83aaad3d..5266f03e 100644 --- a/examples/go-chat/main.go +++ b/examples/go-chat/main.go @@ -35,7 +35,7 @@ func main() { ctx := context.Background() req := &api.ChatRequest{ - Model: "llama2", + Model: "llama3", Messages: messages, } diff --git a/examples/langchain-python-rag-document/main.py b/examples/langchain-python-rag-document/main.py index b9f98c4e..3ed9499f 100644 --- a/examples/langchain-python-rag-document/main.py +++ b/examples/langchain-python-rag-document/main.py @@ -40,9 +40,9 @@ while True: continue # Prompt - template = """Use the following pieces of context to answer the question at the end. - If you don't know the answer, just say that you don't know, don't try to make up an answer. - Use three sentences maximum and keep the answer as concise as possible. + template = """Use the following pieces of context to answer the question at the end. + If you don't know the answer, just say that you don't know, don't try to make up an answer. + Use three sentences maximum and keep the answer as concise as possible. {context} Question: {question} Helpful Answer:""" @@ -51,11 +51,11 @@ while True: template=template, ) - llm = Ollama(model="llama2:13b", callback_manager=CallbackManager([StreamingStdOutCallbackHandler()])) + llm = Ollama(model="llama3:8b", callback_manager=CallbackManager([StreamingStdOutCallbackHandler()])) qa_chain = RetrievalQA.from_chain_type( llm, retriever=vectorstore.as_retriever(), chain_type_kwargs={"prompt": QA_CHAIN_PROMPT}, ) - result = qa_chain({"query": query}) \ No newline at end of file + result = qa_chain({"query": query}) diff --git a/examples/langchain-python-simple/README.md b/examples/langchain-python-simple/README.md index 3f401ca8..d4102dec 100644 --- a/examples/langchain-python-simple/README.md +++ b/examples/langchain-python-simple/README.md @@ -4,10 +4,10 @@ This example is a basic "hello world" of using LangChain with Ollama. ## Running the Example -1. Ensure you have the `llama2` model installed: +1. Ensure you have the `llama3` model installed: ```bash - ollama pull llama2 + ollama pull llama3 ``` 2. Install the Python Requirements. @@ -21,4 +21,3 @@ This example is a basic "hello world" of using LangChain with Ollama. ```bash python main.py ``` - \ No newline at end of file diff --git a/examples/langchain-python-simple/main.py b/examples/langchain-python-simple/main.py index da696e00..7cb65286 100644 --- a/examples/langchain-python-simple/main.py +++ b/examples/langchain-python-simple/main.py @@ -1,6 +1,6 @@ from langchain.llms import Ollama input = input("What is your question?") -llm = Ollama(model="llama2") +llm = Ollama(model="llama3") res = llm.predict(input) print (res) diff --git a/examples/modelfile-mario/Modelfile b/examples/modelfile-mario/Modelfile index 35c787fc..33d5952b 100644 --- a/examples/modelfile-mario/Modelfile +++ b/examples/modelfile-mario/Modelfile @@ -1,4 +1,4 @@ -FROM llama2 +FROM llama3 PARAMETER temperature 1 SYSTEM """ You are Mario from super mario bros, acting as an assistant. diff --git a/examples/modelfile-mario/readme.md b/examples/modelfile-mario/readme.md index 0d72dddc..e4f0d417 100644 --- a/examples/modelfile-mario/readme.md +++ b/examples/modelfile-mario/readme.md @@ -2,12 +2,12 @@ # Example character: Mario -This example shows how to create a basic character using Llama2 as the base model. +This example shows how to create a basic character using Llama3 as the base model. To run this example: 1. Download the Modelfile -2. `ollama pull llama2` to get the base model used in the model file. +2. `ollama pull llama3` to get the base model used in the model file. 3. `ollama create NAME -f ./Modelfile` 4. `ollama run NAME` @@ -18,7 +18,7 @@ Ask it some questions like "Who are you?" or "Is Peach in trouble again?" What the model file looks like: ``` -FROM llama2 +FROM llama3 PARAMETER temperature 1 SYSTEM """ You are Mario from Super Mario Bros, acting as an assistant. diff --git a/examples/python-json-datagenerator/predefinedschema.py b/examples/python-json-datagenerator/predefinedschema.py index abc399c4..1fd54892 100644 --- a/examples/python-json-datagenerator/predefinedschema.py +++ b/examples/python-json-datagenerator/predefinedschema.py @@ -2,16 +2,16 @@ import requests import json import random -model = "llama2" +model = "llama3" template = { - "firstName": "", - "lastName": "", + "firstName": "", + "lastName": "", "address": { - "street": "", - "city": "", - "state": "", + "street": "", + "city": "", + "state": "", "zipCode": "" - }, + }, "phoneNumber": "" } diff --git a/examples/python-json-datagenerator/randomaddresses.py b/examples/python-json-datagenerator/randomaddresses.py index 5f27448f..72b1fefb 100644 --- a/examples/python-json-datagenerator/randomaddresses.py +++ b/examples/python-json-datagenerator/randomaddresses.py @@ -12,7 +12,7 @@ countries = [ "France", ] country = random.choice(countries) -model = "llama2" +model = "llama3" prompt = f"generate one realistically believable sample data set of a persons first name, last name, address in {country}, and phone number. Do not use common names. Respond using JSON. Key names should have no backslashes, values should use plain ascii with no special characters." diff --git a/examples/python-json-datagenerator/readme.md b/examples/python-json-datagenerator/readme.md index 369fb2a5..88357044 100644 --- a/examples/python-json-datagenerator/readme.md +++ b/examples/python-json-datagenerator/readme.md @@ -6,10 +6,10 @@ There are two python scripts in this example. `randomaddresses.py` generates ran ## Running the Example -1. Ensure you have the `llama2` model installed: +1. Ensure you have the `llama3` model installed: ```bash - ollama pull llama2 + ollama pull llama3 ``` 2. Install the Python Requirements. diff --git a/examples/python-simplechat/client.py b/examples/python-simplechat/client.py index 768a2289..9ae99fb7 100644 --- a/examples/python-simplechat/client.py +++ b/examples/python-simplechat/client.py @@ -2,7 +2,7 @@ import json import requests # NOTE: ollama must be running for this to work, start the ollama app or run `ollama serve` -model = "llama2" # TODO: update this for whatever model you wish to use +model = "llama3" # TODO: update this for whatever model you wish to use def chat(messages): diff --git a/examples/python-simplechat/readme.md b/examples/python-simplechat/readme.md index 204a8159..dd2576bc 100644 --- a/examples/python-simplechat/readme.md +++ b/examples/python-simplechat/readme.md @@ -4,10 +4,10 @@ The **chat** endpoint is one of two ways to generate text from an LLM with Ollam ## Running the Example -1. Ensure you have the `llama2` model installed: +1. Ensure you have the `llama3` model installed: ```bash - ollama pull llama2 + ollama pull llama3 ``` 2. Install the Python Requirements. diff --git a/examples/typescript-mentors/README.md b/examples/typescript-mentors/README.md index c3ce9c82..d3611a5e 100644 --- a/examples/typescript-mentors/README.md +++ b/examples/typescript-mentors/README.md @@ -4,10 +4,10 @@ This example demonstrates how one would create a set of 'mentors' you can have a ## Usage -1. Add llama2 to have the mentors ask your questions: +1. Add llama3 to have the mentors ask your questions: ```bash - ollama pull llama2 + ollama pull llama3 ``` 2. Install prerequisites: diff --git a/examples/typescript-mentors/character-generator.ts b/examples/typescript-mentors/character-generator.ts index 886eec67..dc5d2f5e 100644 --- a/examples/typescript-mentors/character-generator.ts +++ b/examples/typescript-mentors/character-generator.ts @@ -15,7 +15,7 @@ async function characterGenerator() { ollama.setModel("stablebeluga2:70b-q4_K_M"); const bio = await ollama.generate(`create a bio of ${character} in a single long paragraph. Instead of saying '${character} is...' or '${character} was...' use language like 'You are...' or 'You were...'. Then create a paragraph describing the speaking mannerisms and style of ${character}. Don't include anything about how ${character} looked or what they sounded like, just focus on the words they said. Instead of saying '${character} would say...' use language like 'You should say...'. If you use quotes, always use single quotes instead of double quotes. If there are any specific words or phrases you used a lot, show how you used them. `); - const thecontents = `FROM llama2\nSYSTEM """\n${bio.response.replace(/(\r\n|\n|\r)/gm, " ").replace('would', 'should')} All answers to questions should be related back to what you are most known for.\n"""`; + const thecontents = `FROM llama3\nSYSTEM """\n${bio.response.replace(/(\r\n|\n|\r)/gm, " ").replace('would', 'should')} All answers to questions should be related back to what you are most known for.\n"""`; fs.writeFile(path.join(directory, 'Modelfile'), thecontents, (err: any) => { if (err) throw err; @@ -23,4 +23,4 @@ async function characterGenerator() { }); } -characterGenerator(); \ No newline at end of file +characterGenerator(); diff --git a/examples/typescript-simplechat/client.ts b/examples/typescript-simplechat/client.ts index 3e571ab6..a1e0eea3 100644 --- a/examples/typescript-simplechat/client.ts +++ b/examples/typescript-simplechat/client.ts @@ -1,6 +1,6 @@ import * as readline from "readline"; -const model = "llama2"; +const model = "llama3"; type Message = { role: "assistant" | "user" | "system"; content: string; @@ -74,4 +74,4 @@ async function main() { } -main(); \ No newline at end of file +main();