Instructions to use squ11z1/Hypnos-Colossus-1T with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use squ11z1/Hypnos-Colossus-1T with Transformers:

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

pipe = pipeline("text-generation", model="squ11z1/Hypnos-Colossus-1T", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("squ11z1/Hypnos-Colossus-1T", trust_remote_code=True, device_map="auto")

llama-cpp-python

How to use squ11z1/Hypnos-Colossus-1T with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="squ11z1/Hypnos-Colossus-1T",
	filename="Q3_K_M/Kimi-K2-Thinking-Q3_K_M-00001-of-00011.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use squ11z1/Hypnos-Colossus-1T with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M
# Run inference directly in the terminal:
llama cli -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M
# Run inference directly in the terminal:
./llama-cli -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M

Use Docker

docker model run hf.co/squ11z1/Hypnos-Colossus-1T:Q3_K_M

LM Studio
Jan

vLLM

How to use squ11z1/Hypnos-Colossus-1T with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "squ11z1/Hypnos-Colossus-1T"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "squ11z1/Hypnos-Colossus-1T",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/squ11z1/Hypnos-Colossus-1T:Q3_K_M

SGLang

How to use squ11z1/Hypnos-Colossus-1T 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 "squ11z1/Hypnos-Colossus-1T" \
    --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": "squ11z1/Hypnos-Colossus-1T",
		"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 "squ11z1/Hypnos-Colossus-1T" \
        --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": "squ11z1/Hypnos-Colossus-1T",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use squ11z1/Hypnos-Colossus-1T with Ollama:
```
ollama run hf.co/squ11z1/Hypnos-Colossus-1T:Q3_K_M
```

Unsloth Studio

How to use squ11z1/Hypnos-Colossus-1T with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for squ11z1/Hypnos-Colossus-1T to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for squ11z1/Hypnos-Colossus-1T to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for squ11z1/Hypnos-Colossus-1T to start chatting

How to use squ11z1/Hypnos-Colossus-1T with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "squ11z1/Hypnos-Colossus-1T:Q3_K_M"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use squ11z1/Hypnos-Colossus-1T with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default squ11z1/Hypnos-Colossus-1T:Q3_K_M

Run Hermes

hermes

Atomic Chat new

OpenClaw new

How to use squ11z1/Hypnos-Colossus-1T with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf squ11z1/Hypnos-Colossus-1T:Q3_K_M

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "squ11z1/Hypnos-Colossus-1T:Q3_K_M" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

Docker Model Runner
How to use squ11z1/Hypnos-Colossus-1T with Docker Model Runner:
```
docker model run hf.co/squ11z1/Hypnos-Colossus-1T:Q3_K_M
```

Lemonade

How to use squ11z1/Hypnos-Colossus-1T with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull squ11z1/Hypnos-Colossus-1T:Q3_K_M

Run and chat with the model

lemonade run user.Hypnos-Colossus-1T-Q3_K_M

List all available models

lemonade list

squ11z1 commited on Dec 21, 2025

Commit

2069488

verified ·

1 Parent(s): 9421f65

Upload config.json with huggingface_hub

Browse files

Files changed (1) hide show

config.json +152 -0

config.json ADDED Viewed

	@@ -0,0 +1,152 @@

+{
+  "_attn_implementation_autoset": false,
+  "_name_or_path": "squ11z1/Hypnos-Colossus-1T",
+  "add_cross_attention": false,
+  "architectures": [
+    "DeepseekV3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "auto_map": {
+    "AutoConfig": "configuration_deepseek.DeepseekV3Config",
+    "AutoModel": "modeling_deepseek.DeepseekV3Model",
+    "AutoModelForCausalLM": "modeling_deepseek.DeepseekV3ForCausalLM"
+  },
+  "aux_loss_alpha": 0.001,
+  "bad_words_ids": null,
+  "begin_suppress_tokens": null,
+  "bos_token_id": 163584,
+  "chunk_size_feed_forward": 0,
+  "cross_attention_hidden_size": null,
+  "decoder_start_token_id": null,
+  "diversity_penalty": 0.0,
+  "do_sample": false,
+  "early_stopping": false,
+  "encoder_no_repeat_ngram_size": 0,
+  "eos_token_id": 163586,
+  "ep_size": 1,
+  "exponential_decay_length_penalty": null,
+  "finetuning_task": null,
+  "first_k_dense_replace": 1,
+  "forced_bos_token_id": null,
+  "forced_eos_token_id": null,
+  "hidden_act": "silu",
+  "hidden_size": 7168,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 18432,
+  "is_decoder": false,
+  "is_encoder_decoder": false,
+  "kv_lora_rank": 512,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1
+  },
+  "length_penalty": 1.0,
+  "max_length": 20,
+  "max_position_embeddings": 262144,
+  "min_length": 0,
+  "model_type": "kimi_k2",
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+  "moe_layer_freq": 1,
+  "n_group": 1,
+  "n_routed_experts": 384,
+  "n_shared_experts": 1,
+  "no_repeat_ngram_size": 0,
+  "norm_topk_prob": true,
+  "num_attention_heads": 64,
+  "num_beam_groups": 1,
+  "num_beams": 1,
+  "num_experts_per_tok": 8,
+  "num_hidden_layers": 61,
+  "num_key_value_heads": 64,
+  "num_nextn_predict_layers": 0,
+  "num_return_sequences": 1,
+  "output_attentions": false,
+  "output_hidden_states": false,
+  "output_scores": false,
+  "pad_token_id": 163839,
+  "prefix": null,
+  "pretraining_tp": 1,
+  "problem_type": null,
+  "pruned_heads": {},
+  "q_lora_rank": 1536,
+  "qk_nope_head_dim": 128,
+  "qk_rope_head_dim": 64,
+  "quantization_config": {
+    "config_groups": {
+      "group_0": {
+        "input_activations": null,
+        "output_activations": null,
+        "targets": [
+          "Linear"
+        ],
+        "weights": {
+          "actorder": null,
+          "block_structure": null,
+          "dynamic": false,
+          "group_size": 32,
+          "num_bits": 4,
+          "observer": "minmax",
+          "observer_kwargs": {},
+          "strategy": "group",
+          "symmetric": true,
+          "type": "int"
+        }
+      }
+    },
+    "format": "pack-quantized",
+    "ignore": [
+      "lm_head",
+      "re:.*self_attn.*",
+      "re:.*shared_experts.*",
+      "re:.*mlp\\.(gate|up|gate_up|down)_proj.*"
+    ],
+    "kv_cache_scheme": null,
+    "quant_method": "compressed-tensors",
+    "quantization_status": "compressed"
+  },
+  "remove_invalid_values": false,
+  "repetition_penalty": 1.0,
+  "return_dict": true,
+  "return_dict_in_generate": false,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "beta_fast": 1.0,
+    "beta_slow": 1.0,
+    "factor": 64.0,
+    "mscale": 1.0,
+    "mscale_all_dim": 1.0,
+    "original_max_position_embeddings": 4096,
+    "type": "yarn"
+  },
+  "rope_theta": 50000.0,
+  "routed_scaling_factor": 2.827,
+  "scoring_func": "sigmoid",
+  "sep_token_id": null,
+  "seq_aux": true,
+  "suppress_tokens": null,
+  "task_specific_params": null,
+  "temperature": 1.0,
+  "tf_legacy_loss": false,
+  "tie_encoder_decoder": false,
+  "tie_word_embeddings": false,
+  "tokenizer_class": null,
+  "top_k": 50,
+  "top_p": 1.0,
+  "topk_group": 1,
+  "topk_method": "noaux_tc",
+  "torch_dtype": "bfloat16",
+  "torchscript": false,
+  "transformers_version": "4.51.3",
+  "typical_p": 1.0,
+  "use_bfloat16": false,
+  "use_cache": true,
+  "v_head_dim": 128,
+  "vocab_size": 163840,
+  "quantum_backend": "ibm_fez",
+  "quantization_method": "INT4 Native + Quantum Scale Perturbation"
+}