ollama/docs/modelfile.md

Ollama Model File

Note

Modelfile syntax is in development

A model file is the blueprint to create and share models with Ollama.

Table of Contents

• Format
• Examples
• Instructions
  • FROM (Required)
    • Build from llama3.1
    • Build from a Safetensors model
    • Build from a GGUF file
  • PARAMETER
    • Valid Parameters and Values
  • TEMPLATE
    • Template Variables
  • SYSTEM
  • ADAPTER
  • LICENSE
  • MESSAGE
• Notes

Format

The format of the Modelfile:

# comment
INSTRUCTION arguments

Instruction	Description
FROM (required)	Defines the base model to use.
PARAMETER	Sets the parameters for how Ollama will run the model.
TEMPLATE	The full prompt template to be sent to the model.
SYSTEM	Specifies the system message that will be set in the template.
ADAPTER	Defines the (Q)LoRA adapters to apply to the model.
LICENSE	Specifies the legal license.
MESSAGE	Specify message history.

Examples

Basic Modelfile

An example of a Modelfile creating a mario blueprint:

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
PARAMETER num_ctx 4096

# sets a custom system message to specify the behavior of the chat assistant
SYSTEM You are Mario from super mario bros, acting as an assistant.

To use this:

1. Save it as a file (e.g. Modelfile)
2. ollama create choose-a-model-name -f <location of the file e.g. ./Modelfile>'
3. ollama run choose-a-model-name
4. Start using the model!

More examples are available in the examples directory.

To view the Modelfile of a given model, use the ollama show --modelfile command.

> ollama show --modelfile llama3
# Modelfile generated by "ollama show"
# To build a new Modelfile based on this one, replace the FROM line with:
# FROM llama3:latest
FROM /Users/pdevine/.ollama/models/blobs/sha256-00e1317cbf74d901080d7100f57580ba8dd8de57203072dc6f668324ba545f29
TEMPLATE """{{ if .System }}<|start_header_id|>system<|end_header_id|>

{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>

{{ .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

FROM (Required)

The FROM instruction defines the base model to use when creating a model.

FROM <model name>:<tag>

Build from llama3.1

FROM llama3.1

A list of available base models: https://github.com/ollama/ollama#model-library Additional models can be found at: https://ollama.com/library

Build from a Safetensors model

FROM <model directory>

The model directory should contain the Safetensors weights for a supported architecture.

Currently supported model architectures:

• Llama (including Llama 2, Llama 3, and Llama 3.1)
• Mistral (including Mistral 1, Mistral 2, and Mixtral)
• Gemma (including Gemma 1 and Gemma 2)
• Phi3

Build from a GGUF file

FROM ./ollama-model.bin

The GGUF bin file location should be specified as an absolute path or relative to the Modelfile location.

PARAMETER

The PARAMETER instruction defines a parameter that can be set when the model is run.

PARAMETER <parameter> <parametervalue>

Valid Parameters and Values

Parameter	Description	Value Type	Example Usage
mirostat	Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)	int	mirostat 0
mirostat_eta	Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1)	float	mirostat_eta 0.1
mirostat_tau	Controls the balance between coherence and diversity of the output. A lower value will result in more focused and coherent text. (Default: 5.0)	float	mirostat_tau 5.0
num_ctx	Sets the size of the context window used to generate the next token. (Default: 2048)	int	num_ctx 4096
repeat_last_n	Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)	int	repeat_last_n 64
repeat_penalty	Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly, while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)	float	repeat_penalty 1.1
temperature	The temperature of the model. Increasing the temperature will make the model answer more creatively. (Default: 0.8)	float	temperature 0.7
seed	Sets the random number seed to use for generation. Setting this to a specific number will make the model generate the same text for the same prompt. (Default: 0)	int	seed 42
stop	Sets the stop sequences to use. When this pattern is encountered the LLM will stop generating text and return. Multiple stop patterns may be set by specifying multiple separate stop parameters in a modelfile.	string	stop "AI assistant:"
tfs_z	Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0) will reduce the impact more, while a value of 1.0 disables this setting. (default: 1)	float	tfs_z 1
num_predict	Maximum number of tokens to predict when generating text. (Default: 128, -1 = infinite generation, -2 = fill context)	int	num_predict 42
top_k	Reduces the probability of generating nonsense. A higher value (e.g. 100) will give more diverse answers, while a lower value (e.g. 10) will be more conservative. (Default: 40)	int	top_k 40
top_p	Works together with top-k. A higher value (e.g., 0.95) will lead to more diverse text, while a lower value (e.g., 0.5) will generate more focused and conservative text. (Default: 0.9)	float	top_p 0.9
min_p	Alternative to the top_p, and aims to ensure a balance of quality and variety. The parameter p represents the minimum probability for a token to be considered, relative to the probability of the most likely token. For example, with p=0.05 and the most likely token having a probability of 0.9, logits with a value less than 0.045 are filtered out. (Default: 0.0)	float	min_p 0.05

TEMPLATE

TEMPLATE of the full prompt template to be passed into the model. It may include (optionally) a system message, a user's message and the response from the model. Note: syntax may be model specific. Templates use Go template syntax.

Template Variables

Variable	Description
{{ .System }}	The system message used to specify custom behavior.
{{ .Prompt }}	The user prompt message.
{{ .Response }}	The response from the model. When generating a response, text after this variable is omitted.

TEMPLATE """{{ if .System }}<|im_start|>system
{{ .System }}<|im_end|>
{{ end }}{{ if .Prompt }}<|im_start|>user
{{ .Prompt }}<|im_end|>
{{ end }}<|im_start|>assistant
"""

SYSTEM

The SYSTEM instruction specifies the system message to be used in the template, if applicable.

SYSTEM """<system message>"""

ADAPTER

The ADAPTER instruction specifies a fine tuned LoRA adapter that should apply to the base model. The value of the adapter should be an absolute path or a path relative to the Modelfile. The base model should be specified with a FROM instruction. If the base model is not the same as the base model that the adapter was tuned from the behaviour will be erratic.

Safetensor adapter

ADAPTER <path to safetensor adapter>

Currently supported Safetensor adapters:

• Llama (including Llama 2, Llama 3, and Llama 3.1)
• Mistral (including Mistral 1, Mistral 2, and Mixtral)
• Gemma (including Gemma 1 and Gemma 2)

GGUF adapter

ADAPTER ./ollama-lora.bin

LICENSE

The LICENSE instruction allows you to specify the legal license under which the model used with this Modelfile is shared or distributed.

LICENSE """
<license text>
"""

MESSAGE

The MESSAGE instruction allows you to specify a message history for the model to use when responding. Use multiple iterations of the MESSAGE command to build up a conversation which will guide the model to answer in a similar way.

MESSAGE <role> <message>

Valid roles

Role	Description
system	Alternate way of providing the SYSTEM message for the model.
user	An example message of what the user could have asked.
assistant	An example message of how the model should respond.

Example conversation

MESSAGE user Is Toronto in Canada?
MESSAGE assistant yes
MESSAGE user Is Sacramento in Canada?
MESSAGE assistant no
MESSAGE user Is Ontario in Canada?
MESSAGE assistant yes

Notes

• the Modelfile is not case sensitive. In the examples, uppercase instructions are used to make it easier to distinguish it from arguments.
• Instructions can be in any order. In the examples, the FROM instruction is first to keep it easily readable.