Instructions to use allenai/Bolmo-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use allenai/Bolmo-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="allenai/Bolmo-7B", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("allenai/Bolmo-7B", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use allenai/Bolmo-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "allenai/Bolmo-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "allenai/Bolmo-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/allenai/Bolmo-7B
- SGLang
How to use allenai/Bolmo-7B 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 "allenai/Bolmo-7B" \ --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": "allenai/Bolmo-7B", "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 "allenai/Bolmo-7B" \ --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": "allenai/Bolmo-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use allenai/Bolmo-7B with Docker Model Runner:
docker model run hf.co/allenai/Bolmo-7B
| { | |
| "add_expanded_embeddings": true, | |
| "architectures": [ | |
| "BolmoForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "auto_map": { | |
| "AutoConfig": "configuration_bolmo.BolmoConfig", | |
| "AutoModelForCausalLM": "modeling_bolmo.BolmoForCausalLM" | |
| }, | |
| "bos_token_id": 1, | |
| "boundary_predictor_lookahead": 1, | |
| "boundary_threshold": "sample:0", | |
| "dtype": "float32", | |
| "eos_token_id": 1, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 11008, | |
| "layer_types": [ | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "sliding_attention", | |
| "full_attention" | |
| ], | |
| "local_intermediate_size": 5504, | |
| "local_rms_norm_eps": 1e-05, | |
| "max_position_embeddings": 65536, | |
| "model_type": "bolmo", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 32, | |
| "num_local_decoder_layers": 4, | |
| "num_local_encoder_layers": 1, | |
| "num_local_heads": 16, | |
| "pad_token_id": 0, | |
| "rms_norm_eps": 1e-06, | |
| "rope_scaling": { | |
| "attention_factor": 1.2079441541679836, | |
| "beta_fast": 32, | |
| "beta_slow": 1, | |
| "factor": 8.0, | |
| "original_max_position_embeddings": 8192, | |
| "rope_type": "yarn" | |
| }, | |
| "rope_theta": 500000, | |
| "sliding_window": 4096, | |
| "subword_vocab_size": 100278, | |
| "tie_word_embeddings": false, | |
| "tokenizer_config": { | |
| "bos_token_id": 1, | |
| "bpe_token_end_id": 3, | |
| "eos_token_id": 1, | |
| "original_identifier": "allenai/dolma2-tokenizer", | |
| "pad_token_id": 0, | |
| "special_tokens": [ | |
| "<pad>", | |
| "<bos>", | |
| "<eos>", | |
| "<bpe_token_end>" | |
| ], | |
| "special_tokens_first": true, | |
| "vocab_size": 520 | |
| }, | |
| "transformers_version": "4.57.3", | |
| "use_cache": true, | |
| "vocab_size": 520 | |
| } | |