Text Generation
Transformers
Safetensors
English
jarvis_titan_moe
Mixture of Experts
deepseek-moe
titans-neural-memory
tri-brid-memory
differential-holographic-attention
dha-3
csa3-perturbative-attention
multi-token-prediction
reasoning
math
code
agentic
long-context
conversational
custom_code
Instructions to use dhanesh-hf/Jarvis-Titan-M4-Activated with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dhanesh-hf/Jarvis-Titan-M4-Activated with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dhanesh-hf/Jarvis-Titan-M4-Activated", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("dhanesh-hf/Jarvis-Titan-M4-Activated", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dhanesh-hf/Jarvis-Titan-M4-Activated with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dhanesh-hf/Jarvis-Titan-M4-Activated" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dhanesh-hf/Jarvis-Titan-M4-Activated", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/dhanesh-hf/Jarvis-Titan-M4-Activated
- SGLang
How to use dhanesh-hf/Jarvis-Titan-M4-Activated 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 "dhanesh-hf/Jarvis-Titan-M4-Activated" \ --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": "dhanesh-hf/Jarvis-Titan-M4-Activated", "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 "dhanesh-hf/Jarvis-Titan-M4-Activated" \ --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": "dhanesh-hf/Jarvis-Titan-M4-Activated", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use dhanesh-hf/Jarvis-Titan-M4-Activated with Docker Model Runner:
docker model run hf.co/dhanesh-hf/Jarvis-Titan-M4-Activated
Download tokenizer_config.json from dhanesh-hf/Jarvis-Titan-M4-Activated: direct link, hf CLI and curl.
- Browser
- Download file 3.66 kB
-
https://huggingface.co/dhanesh-hf/Jarvis-Titan-M4-Activated/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://dhanesh-hf/Jarvis-Titan-M4-Activated/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/dhanesh-hf/Jarvis-Titan-M4-Activated/resolve/main/tokenizer_config.json
3.66 kB
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": null, | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|im_end|>", | |
| "errors": "replace", | |
| "is_local": true, | |
| "local_files_only": true, | |
| "model_max_length": 131072, | |
| "pad_token": "<|endoftext|>", | |
| "split_special_tokens": false, | |
| "tokenizer_class": "Qwen2Tokenizer", | |
| "unk_token": null, | |
| "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'You are J.A.R.V.I.S., an expert autonomous intelligence agent engineered by Dhanesh. You have access to functions provided in <tools>...</tools> to execute actions deterministically and eliminate hallucinations. Always think before calling a tool inside <think>...</think> tags. When you receive a <tool_response>, verify the results before finalizing your response in <answer>...</answer>.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user request.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n {%- if messages[0]['role'] == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0]['content'] + '<|im_end|>\\n' }}\n {%- else %}\n {{- '<|im_start|>system\\nYou are J.A.R.V.I.S., an expert reasoning assistant engineered by Dhanesh. Before answering, think through the problem carefully inside <think>...</think> tags. Verify your reasoning. If you detect a flaw, correct it. Provide your final solution inside <answer>...</answer> tags. When the problem asks for a boxed answer, use \\\\boxed{your answer}. Be concise but complete.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n<tool_call>\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n</tool_call>' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n<tool_response>\\n' }}\n {{- message.content }}\n {{- '\\n</tool_response>' }}\n {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n {{- '<|im_end|>\\n' }}\n {%- endif %}\n {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n {{- '<|im_start|>assistant\\n' }}\n{%- endif %}\n" | |
| } |