Tools 8B

14 Pulls Updated 6 weeks ago

6 weeks ago

9d3885b4f4a2 · 16GB

model
llama
·
8.03B
·
F16
params
{"stop":["<|start_header_id|>","<|end_header_id|>","<|eot_id|>"]}
template
{{ if .Messages }} {{- if or .System .Tools }}<|start_header_id|>system<|end_header_id|> {{- if .System }} {{ .System }} {{- end }} {{- if .Tools }} You are a helpful assistant with tool calling capabilities. When you receive a tool call response, use the output to format an answer to the orginal use question. {{- end }}<|eot_id|> {{- end }} {{- range $i, $_ := .Messages }} {{- $last := eq (len (slice $.Messages $i)) 1 }} {{- if eq .Role "user" }}<|start_header_id|>user<|end_header_id|> {{- if and $.Tools $last }} Given the following functions, please respond with a JSON for a function call with its proper arguments that best answers the given prompt. Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. Do not use variables. {{ $.Tools }} {{- end }} {{ .Content }}<|eot_id|>{{ if $last }}<|start_header_id|>assistant<|end_header_id|> {{ end }} {{- else if eq .Role "assistant" }}<|start_header_id|>assistant<|end_header_id|> {{- if .ToolCalls }} {{- range .ToolCalls }}{"name": "{{ .Function.Name }}", "parameters": {{ .Function.Arguments }}}{{ end }} {{- else }} {{ .Content }}{{ if not $last }}<|eot_id|>{{ end }} {{- end }} {{- else if eq .Role "tool" }}<|start_header_id|>ipython<|end_header_id|> {{ .Content }}<|eot_id|>{{ if $last }}<|start_header_id|>assistant<|end_header_id|> {{ end }} {{- end }} {{- end }} {{- else }} {{- 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|> {{ end }}{{ .Response }}{{ if .Response }}<|eot_id|>{{ end }}

Readme

Arcee Spark

Llama-Spark is a powerful conversational AI model developed by Arcee.ai. It’s built on the foundation of Llama-3.1-8B and merges the power of our Tome Dataset with Llama-3.1-8B-Instruct, resulting in a remarkable conversationalist that punches well above its 8B parameter weight class.

Model Description

Llama-Spark is our commitment to consistently delivering the best-performing conversational AI in the 6-9B parameter range. As new base models become available, we’ll continue to update and improve Spark to maintain its leadership position.

This model is a successor to our original Arcee-Spark, incorporating advancements and learnings from our ongoing research and development.

Intended Uses

Llama-Spark is intended for use in conversational AI applications, such as chatbots, virtual assistants, and dialogue systems. It excels at engaging in natural and informative conversations.

Training Information

Llama-Spark is built upon the Llama-3.1-8B base model, fine-tuned using of the Tome Dataset and merged with Llama-3.1-8B-Instruct.

Evaluation Results

Please note that these scores are consistantly higher than the OpenLLM leaderboard, and should be compared to their relative performance increase not weighed against the leaderboard.


Arcee Spark

Acknowledgements

We extend our deepest gratitude to PrimeIntellect for being our compute sponsor for this project.

https://huggingface.co/arcee-ai/Llama-Spark