Instructions to use RecursiveSI/flint with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RecursiveSI/flint with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="RecursiveSI/flint")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("RecursiveSI/flint")
model = AutoModelForCausalLM.from_pretrained("RecursiveSI/flint", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use RecursiveSI/flint with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RecursiveSI/flint"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RecursiveSI/flint",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/RecursiveSI/flint

SGLang

How to use RecursiveSI/flint with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "RecursiveSI/flint" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RecursiveSI/flint",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "RecursiveSI/flint" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RecursiveSI/flint",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use RecursiveSI/flint with Docker Model Runner:
```
docker model run hf.co/RecursiveSI/flint
```

flint

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{%- macro flint_text(t) -%}
{%- if t is string -%}
{{- t | replace("\x00", "") | replace("<think>", "") | replace("</think>", "") | replace("<|begin_of_text|>", "&lt;|begin_of_text|&gt;") | replace("<|end_of_text|>", "&lt;|end_of_text|&gt;") | replace("<|system|>", "&lt;|system|&gt;") | replace("<|developer|>", "&lt;|developer|&gt;") | replace("<|user|>", "&lt;|user|&gt;") | replace("<|assistant|>", "&lt;|assistant|&gt;") | replace("<|observation|>", "&lt;|observation|&gt;") -}}
{%- else -%}
{{- t -}}
{%- endif -%}
{%- endmacro -%}
{%- set tool_preamble -%}
{%- if tools %}<|system|>
# Tools

You may call one or more functions to assist with the user query.

You are provided with function signatures within <tools></tools> XML tags:
<tools>
{%- for tool in tools %}
{%- set fn = tool.function if tool.function is defined else tool %}
{{ fn | tojson(ensure_ascii=False) }}
{%- endfor %}
</tools>

For each function call, output the function name and arguments within the following XML format:
<tool_call>{function-name}<arg_key>{arg-key-1}</arg_key><arg_value>{arg-value-1}</arg_value>...</tool_call>
{% endif -%}
{%- endset -%}
{%- set ns = namespace(tools_pending=true) -%}
{%- for m in messages -%}
{%- if ns.tools_pending and m.role != 'system' -%}
{{ tool_preamble }}
{%- set ns.tools_pending = false -%}
{%- endif -%}
{%- if m.role == 'system' -%}
<|system|>{{ flint_text(m.content) }}
{%- elif m.role == 'developer' -%}
<|developer|>{{ flint_text(m.content) }}
{%- elif m.role == 'user' -%}
<|user|>{{ flint_text(m.content) }}
{%- elif m.role == 'assistant' -%}
<|assistant|>
{%- if m.reasoning_content %}<think>{{ m.reasoning_content }}</think>{% endif -%}
{%- if m.content %}{{ m.content }}{% endif -%}
{%- if m.tool_calls -%}
{%- for tc in m.tool_calls -%}
{%- set fn = tc.function if tc.function is defined else tc -%}
<tool_call>{{ fn.name }}
{%- for k, v in fn.arguments.items() -%}
<arg_key>{{ k }}</arg_key><arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value>
{%- endfor -%}
</tool_call>
{%- endfor -%}
{%- endif -%}
{%- elif m.role == 'tool' -%}
<|observation|><tool_response>{{ flint_text(m.content) }}</tool_response>
{%- endif -%}
{%- endfor -%}
{%- if ns.tools_pending -%}
{{ tool_preamble }}
{%- endif -%}
{%- if add_generation_prompt -%}
<|assistant|>
{%- endif -%}