Instructions to use Codemaster67/Olmo-1b_token_extension_modern_molbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Codemaster67/Olmo-1b_token_extension_modern_molbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Codemaster67/Olmo-1b_token_extension_modern_molbert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Codemaster67/Olmo-1b_token_extension_modern_molbert") model = AutoModelForCausalLM.from_pretrained("Codemaster67/Olmo-1b_token_extension_modern_molbert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Codemaster67/Olmo-1b_token_extension_modern_molbert with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Codemaster67/Olmo-1b_token_extension_modern_molbert" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Codemaster67/Olmo-1b_token_extension_modern_molbert", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Codemaster67/Olmo-1b_token_extension_modern_molbert
- SGLang
How to use Codemaster67/Olmo-1b_token_extension_modern_molbert 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 "Codemaster67/Olmo-1b_token_extension_modern_molbert" \ --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": "Codemaster67/Olmo-1b_token_extension_modern_molbert", "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 "Codemaster67/Olmo-1b_token_extension_modern_molbert" \ --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": "Codemaster67/Olmo-1b_token_extension_modern_molbert", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Codemaster67/Olmo-1b_token_extension_modern_molbert with Docker Model Runner:
docker model run hf.co/Codemaster67/Olmo-1b_token_extension_modern_molbert
Download config.json from Codemaster67/Olmo-1b_token_extension_modern_molbert: direct link, hf CLI and curl.
- Browser
- Download file 683 Bytes
-
https://huggingface.co/Codemaster67/Olmo-1b_token_extension_modern_molbert/resolve/main/config.json
- Command line
-
hf download hf://Codemaster67/Olmo-1b_token_extension_modern_molbert/config.json
-
curl -L -o config.json https://huggingface.co/Codemaster67/Olmo-1b_token_extension_modern_molbert/resolve/main/config.json
683 Bytes
| { | |
| "architectures": [ | |
| "OlmoForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": null, | |
| "clip_qkv": null, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 50279, | |
| "hidden_act": "silu", | |
| "hidden_size": 2048, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 8192, | |
| "max_position_embeddings": 2048, | |
| "model_type": "olmo", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 16, | |
| "num_key_value_heads": 16, | |
| "pad_token_id": 1, | |
| "pretraining_tp": 1, | |
| "rope_parameters": { | |
| "rope_theta": 10000.0, | |
| "rope_type": "default" | |
| }, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.0.0", | |
| "use_cache": true, | |
| "vocab_size": 51617 | |
| } | |