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)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("allenai/Bolmo-7B", trust_remote_code=True, device_map="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
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"add_expanded_embeddings": true,
"architectures": [
"BolmoForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"auto_map": {
"AutoConfig": "configuration_bolmo.BolmoConfig",
"AutoModelForCausalLM": "modeling_bolmo.BolmoForCausalLM"
},
"block_type": "reordered_norm",
"bos_token_id": 1,
"boundary_predictor_lookahead": 1,
"boundary_threshold": "sample:0",
"dtype": "float32",
"eos_token_id": 1,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 4096,
"initializer_range": 0.02,
"intermediate_size": 11008,
"layer_types": [
"sliding_attention",
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"full_attention",
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"full_attention",
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"full_attention"
],
"local_intermediate_size": 5504,
"local_rms_norm_eps": 1e-05,
"max_position_embeddings": 65536,
"model_type": "bolmo",
"norm_type": "rms",
"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": null,
"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,
"use_head_qk_norm": false,
"use_qk_norm": true,
"vocab_size": 520
}
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