Instructions to use trl-internal-testing/tiny-FalconMambaForCausalLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use trl-internal-testing/tiny-FalconMambaForCausalLM with Transformers:

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

pipe = pipeline("text-generation", model="trl-internal-testing/tiny-FalconMambaForCausalLM")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("trl-internal-testing/tiny-FalconMambaForCausalLM")
model = AutoModelForCausalLM.from_pretrained("trl-internal-testing/tiny-FalconMambaForCausalLM")
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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use trl-internal-testing/tiny-FalconMambaForCausalLM with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/trl-internal-testing/tiny-FalconMambaForCausalLM

SGLang

How to use trl-internal-testing/tiny-FalconMambaForCausalLM 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 "trl-internal-testing/tiny-FalconMambaForCausalLM" \
    --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": "trl-internal-testing/tiny-FalconMambaForCausalLM",
		"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 "trl-internal-testing/tiny-FalconMambaForCausalLM" \
        --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": "trl-internal-testing/tiny-FalconMambaForCausalLM",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use trl-internal-testing/tiny-FalconMambaForCausalLM with Docker Model Runner:
```
docker model run hf.co/trl-internal-testing/tiny-FalconMambaForCausalLM
```

qgallouedec HF Staff commited on Sep 24, 2025

Commit

148d3c8

verified ·

1 Parent(s): 88e0b1b

Upload FalconMambaForCausalLM

Browse files

Files changed (3) hide show

config.json +4 -4
generation_config.json +1 -1
model.safetensors +2 -2

config.json CHANGED Viewed

@@ -4,12 +4,13 @@
   ],
   "bos_token_id": 0,
   "conv_kernel": 4,
   "eos_token_id": 0,
   "expand": 2,
   "hidden_act": "silu",
   "hidden_size": 8,
   "initializer_range": 0.1,
-  "intermediate_size": 16,
   "layer_norm_epsilon": 1e-05,
   "mixer_rms_eps": 1e-06,
   "model_type": "falcon_mamba",
@@ -26,11 +27,10 @@
   "time_step_min": 0.001,
   "time_step_rank": 1,
   "time_step_scale": 1.0,
-  "torch_dtype": "float32",
-  "transformers_version": "4.55.0.dev0",
   "use_bias": false,
   "use_cache": true,
   "use_conv_bias": true,
   "use_falcon_mambapy": false,
-  "vocab_size": 65036
 }

   ],
   "bos_token_id": 0,
   "conv_kernel": 4,
+  "dtype": "float32",
   "eos_token_id": 0,
   "expand": 2,
   "hidden_act": "silu",
   "hidden_size": 8,
   "initializer_range": 0.1,
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   "layer_norm_epsilon": 1e-05,
   "mixer_rms_eps": 1e-06,
   "model_type": "falcon_mamba",
   "time_step_min": 0.001,
   "time_step_rank": 1,
   "time_step_scale": 1.0,
+  "transformers_version": "4.57.0.dev0",
   "use_bias": false,
   "use_cache": true,
   "use_conv_bias": true,
   "use_falcon_mambapy": false,
+  "vocab_size": 65024
 }

generation_config.json CHANGED Viewed

@@ -3,5 +3,5 @@
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   "eos_token_id": 0,
   "pad_token_id": 0,
-  "transformers_version": "4.55.0.dev0"
 }

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   "eos_token_id": 0,
   "pad_token_id": 0,
+  "transformers_version": "4.57.0.dev0"
 }

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