Instructions to use modrill/math-think-q8b-20260908 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use modrill/math-think-q8b-20260908 with Transformers:

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

pipe = pipeline("text-generation", model="modrill/math-think-q8b-20260908")
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("modrill/math-think-q8b-20260908")
model = AutoModelForCausalLM.from_pretrained("modrill/math-think-q8b-20260908", 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 modrill/math-think-q8b-20260908 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "modrill/math-think-q8b-20260908"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "modrill/math-think-q8b-20260908",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/modrill/math-think-q8b-20260908

SGLang

How to use modrill/math-think-q8b-20260908 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 "modrill/math-think-q8b-20260908" \
    --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": "modrill/math-think-q8b-20260908",
		"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 "modrill/math-think-q8b-20260908" \
        --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": "modrill/math-think-q8b-20260908",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use modrill/math-think-q8b-20260908 with Docker Model Runner:
```
docker model run hf.co/modrill/math-think-q8b-20260908
```

math-think-q8b-20260908 / COMMIT.json

modrill

freeze: Think 2ep merged endpoint + LoRA adapter for modrill/think-src-q8b-20260908

9b62295 verified about 2 months ago

Raw History Blame Contribute Delete

3.93 kB

{
  "schema": "ddc-atomic-checkpoint-commit/1",
  "runner_id": "THINK_B_2EP_SIX_ARMS_RUNNER_V3",
  "completed_optimizer_updates": 977,
  "cumulative_realized_active_tokens": 63999854,
  "bindings": {
    "config_sha256": "c505bc2c9b1f670ea4fa5fdcdde576289997123ea814bbb0f42c6a05a40f960c",
    "runner_code_sha256": "fd6d1c6403810acc4460e2ce0fb5f4418881387b11f4bd21f7cd21067faa3a0a",
    "config_schema_sha256": "d6d13eeee42bf04cf34fc68b2fa7a61b316c4543b77d7d779815b8eddf10c099",
    "python_binary_sha256": "5700a6a7804feb44da6c963ebd1323982478b7ca57478e4e81981c47818453bd",
    "environment_lock_sha256": "72288b0cf05c492e5950c02a9e2870593458703c334b0fa7b535c78d299d82b9",
    "base_composite_sha256": "befbd853b79e181a388c379e5ba79df5f628a9390c3dda092266f8c66e0d3a93",
    "base_lock_sha256": "7cbc0ab33bbfcbd2158665bf0d58ae8730419a383564b379d28e31889f838e04",
    "frozen_rows_sha256": "32b89ef654bc0176a534679dd2d07bf1dc6e5b24a51bad882186fa49b893fec7",
    "ordered_ids_sha256": "bd5107fe70b053c9de462099b549fd7114320714ac816890782ec241011a9bee",
    "update_plan_sha256": "6ce190fa443f4ccb9e69600ac38c8a0f905e802b9c86c71414aad777de8d35ad",
    "data_receipt_sha256": "e66346fb413557929ab53648bc656fb3102557cf3460abb49c7b1c6e7281420d",
    "decontamination_receipt_sha256": "66c360871b06208ed20e473e57ad0f09c79e4dac1b3124a9461a5b729b487153",
    "render_receipt_sha256": "e66346fb413557929ab53648bc656fb3102557cf3460abb49c7b1c6e7281420d",
    "token_bake_sha256": "74234e98afe7498fb5daf1f36ac2d78acc339464f950703b8c019892f982b90b",
    "continuation_sha256": "74234e98afe7498fb5daf1f36ac2d78acc339464f950703b8c019892f982b90b"
  },
  "trainer_state": {
    "path": "trainer_state.pt",
    "bytes": 2095983309,
    "sha256": "faff647c9e560b03a5fde27360ded827a19b48e10a9dc8c26262bc22b16aa6b9"
  },
  "token_boundary_ledger": {
    "path": "TOKEN_BOUNDARY_LEDGER.json",
    "bytes": 972202,
    "sha256": "c90bb9ad2cb0449f59409d708ef155d4f2d51620bfd0a0dfb4237eb8515e66d7"
  },
  "adapter_files": [
    {
      "path": "adapter/README.md",
      "bytes": 5414,
      "sha256": "d5c55db9b0c9dfaf151b29b6579980758d75cbca5e0718b786f2b29badaadb5d"
    },
    {
      "path": "adapter/adapter_config.json",
      "bytes": 1398,
      "sha256": "ca7aeabc8ae1fe379d375b01680e0832fea2c721e03328a945ab98b05a747c83"
    },
    {
      "path": "adapter/adapter_model.safetensors",
      "bytes": 698518296,
      "sha256": "19c57c62bf914b008a46ab06330733db7f0bcb58342f2833b512ab0c17058201"
    }
  ],
  "serialization_canary": {
    "save_load_format": "safetensors",
    "state_key_count": 506,
    "token_state": {
      "schema": "think-b-2ep-token-rows/1",
      "tensors": [
        {
          "key": "base_model.model.lm_head.token_adapter.trainable_tokens_delta",
          "sha256": "2809ca4c04b4f3847ad277c815f00f13c7747c2d1db4f6876e42301d5f6f8a0c",
          "shape": [
            3,
            4096
          ],
          "dtype": "torch.float32"
        },
        {
          "key": "base_model.model.model.embed_tokens.token_adapter.trainable_tokens_delta",
          "sha256": "e58013f68b0f61a334ad20e5cf4a6f8d12fe888bca92fc1097b05c6144888eae",
          "shape": [
            3,
            4096
          ],
          "dtype": "torch.float32"
        }
      ]
    }
  },
  "token_state": {
    "schema": "think-b-2ep-token-rows/1",
    "tensors": [
      {
        "key": "base_model.model.lm_head.token_adapter.trainable_tokens_delta",
        "sha256": "2809ca4c04b4f3847ad277c815f00f13c7747c2d1db4f6876e42301d5f6f8a0c",
        "shape": [
          3,
          4096
        ],
        "dtype": "torch.float32"
      },
      {
        "key": "base_model.model.model.embed_tokens.token_adapter.trainable_tokens_delta",
        "sha256": "e58013f68b0f61a334ad20e5cf4a6f8d12fe888bca92fc1097b05c6144888eae",
        "shape": [
          3,
          4096
        ],
        "dtype": "torch.float32"
      }
    ]
  }
}

	{
	"schema": "ddc-atomic-checkpoint-commit/1",
	"runner_id": "THINK_B_2EP_SIX_ARMS_RUNNER_V3",
	"completed_optimizer_updates": 977,
	"cumulative_realized_active_tokens": 63999854,
	"bindings": {
	"config_sha256": "c505bc2c9b1f670ea4fa5fdcdde576289997123ea814bbb0f42c6a05a40f960c",
	"runner_code_sha256": "fd6d1c6403810acc4460e2ce0fb5f4418881387b11f4bd21f7cd21067faa3a0a",
	"config_schema_sha256": "d6d13eeee42bf04cf34fc68b2fa7a61b316c4543b77d7d779815b8eddf10c099",
	"python_binary_sha256": "5700a6a7804feb44da6c963ebd1323982478b7ca57478e4e81981c47818453bd",
	"environment_lock_sha256": "72288b0cf05c492e5950c02a9e2870593458703c334b0fa7b535c78d299d82b9",
	"base_composite_sha256": "befbd853b79e181a388c379e5ba79df5f628a9390c3dda092266f8c66e0d3a93",
	"base_lock_sha256": "7cbc0ab33bbfcbd2158665bf0d58ae8730419a383564b379d28e31889f838e04",
	"frozen_rows_sha256": "32b89ef654bc0176a534679dd2d07bf1dc6e5b24a51bad882186fa49b893fec7",
	"ordered_ids_sha256": "bd5107fe70b053c9de462099b549fd7114320714ac816890782ec241011a9bee",
	"update_plan_sha256": "6ce190fa443f4ccb9e69600ac38c8a0f905e802b9c86c71414aad777de8d35ad",
	"data_receipt_sha256": "e66346fb413557929ab53648bc656fb3102557cf3460abb49c7b1c6e7281420d",
	"decontamination_receipt_sha256": "66c360871b06208ed20e473e57ad0f09c79e4dac1b3124a9461a5b729b487153",
	"render_receipt_sha256": "e66346fb413557929ab53648bc656fb3102557cf3460abb49c7b1c6e7281420d",
	"token_bake_sha256": "74234e98afe7498fb5daf1f36ac2d78acc339464f950703b8c019892f982b90b",
	"continuation_sha256": "74234e98afe7498fb5daf1f36ac2d78acc339464f950703b8c019892f982b90b"
	},
	"trainer_state": {
	"path": "trainer_state.pt",
	"bytes": 2095983309,
	"sha256": "faff647c9e560b03a5fde27360ded827a19b48e10a9dc8c26262bc22b16aa6b9"
	},
	"token_boundary_ledger": {
	"path": "TOKEN_BOUNDARY_LEDGER.json",
	"bytes": 972202,
	"sha256": "c90bb9ad2cb0449f59409d708ef155d4f2d51620bfd0a0dfb4237eb8515e66d7"
	},
	"adapter_files": [
	{
	"path": "adapter/README.md",
	"bytes": 5414,
	"sha256": "d5c55db9b0c9dfaf151b29b6579980758d75cbca5e0718b786f2b29badaadb5d"
	},
	{
	"path": "adapter/adapter_config.json",
	"bytes": 1398,
	"sha256": "ca7aeabc8ae1fe379d375b01680e0832fea2c721e03328a945ab98b05a747c83"
	},
	{
	"path": "adapter/adapter_model.safetensors",
	"bytes": 698518296,
	"sha256": "19c57c62bf914b008a46ab06330733db7f0bcb58342f2833b512ab0c17058201"
	}
	],
	"serialization_canary": {
	"save_load_format": "safetensors",
	"state_key_count": 506,
	"token_state": {
	"schema": "think-b-2ep-token-rows/1",
	"tensors": [
	{
	"key": "base_model.model.lm_head.token_adapter.trainable_tokens_delta",
	"sha256": "2809ca4c04b4f3847ad277c815f00f13c7747c2d1db4f6876e42301d5f6f8a0c",
	"shape": [
	3,
	4096
	],
	"dtype": "torch.float32"
	},
	{
	"key": "base_model.model.model.embed_tokens.token_adapter.trainable_tokens_delta",
	"sha256": "e58013f68b0f61a334ad20e5cf4a6f8d12fe888bca92fc1097b05c6144888eae",
	"shape": [
	3,
	4096
	],
	"dtype": "torch.float32"
	}
	]
	}
	},
	"token_state": {
	"schema": "think-b-2ep-token-rows/1",
	"tensors": [
	{
	"key": "base_model.model.lm_head.token_adapter.trainable_tokens_delta",
	"sha256": "2809ca4c04b4f3847ad277c815f00f13c7747c2d1db4f6876e42301d5f6f8a0c",
	"shape": [
	3,
	4096
	],
	"dtype": "torch.float32"
	},
	{
	"key": "base_model.model.model.embed_tokens.token_adapter.trainable_tokens_delta",
	"sha256": "e58013f68b0f61a334ad20e5cf4a6f8d12fe888bca92fc1097b05c6144888eae",
	"shape": [
	3,
	4096
	],
	"dtype": "torch.float32"
	}
	]
	}
	}