Instructions to use maidacundo/open-mythos-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use maidacundo/open-mythos-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="maidacundo/open-mythos-tiny")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("maidacundo/open-mythos-tiny", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use maidacundo/open-mythos-tiny with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "maidacundo/open-mythos-tiny" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "maidacundo/open-mythos-tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/maidacundo/open-mythos-tiny
- SGLang
How to use maidacundo/open-mythos-tiny 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 "maidacundo/open-mythos-tiny" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "maidacundo/open-mythos-tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "maidacundo/open-mythos-tiny" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "maidacundo/open-mythos-tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use maidacundo/open-mythos-tiny with Docker Model Runner:
docker model run hf.co/maidacundo/open-mythos-tiny
| { | |
| "architectures": [ | |
| "OpenMythosForCausalLM" | |
| ], | |
| "bias": false, | |
| "block_size": 256, | |
| "bos_token_id": 1, | |
| "dtype": "float32", | |
| "effective_expected_depth": 10, | |
| "eos_token_id": 2, | |
| "head_dim": 64, | |
| "init_values": { | |
| "embed_scale": 16.0, | |
| "embedding": 0.03952847075210474, | |
| "out_proj": 0.008838834764831844, | |
| "std": 0.03952847075210474 | |
| }, | |
| "injection_type": "lti", | |
| "intermediate_size": 1024, | |
| "kv_lora_rank": 512, | |
| "mean_backprop_depth": 2, | |
| "mean_recurrence": 4, | |
| "model_type": "open_mythos", | |
| "moe_intermediate_size": 1024, | |
| "moe_top_k": 2, | |
| "n_embd": 256, | |
| "n_heads": 4, | |
| "n_kv_heads": 4, | |
| "n_layers": 4, | |
| "n_layers_in_coda": 1, | |
| "n_layers_in_prelude": 1, | |
| "n_layers_in_recurrent_block": 2, | |
| "n_routed_experts": 8, | |
| "n_shared_experts": 2, | |
| "norm_eps": 1e-06, | |
| "num_key_value_heads": 4, | |
| "pad_token_id": 0, | |
| "q_lora_rank": 1536, | |
| "qk_bias": true, | |
| "rope_base": 50000.0, | |
| "rope_head_dim": 64, | |
| "state_init": "like-init", | |
| "tie_embeddings": true, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.6.0", | |
| "use_cache": false, | |
| "use_mla": false, | |
| "use_moe": false, | |
| "vocab_size": 50257 | |
| } | |