Instructions to use gabrielpickard/bgkit-350m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gabrielpickard/bgkit-350m with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="gabrielpickard/bgkit-350m")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("gabrielpickard/bgkit-350m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use gabrielpickard/bgkit-350m with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "gabrielpickard/bgkit-350m" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "gabrielpickard/bgkit-350m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/gabrielpickard/bgkit-350m
- SGLang
How to use gabrielpickard/bgkit-350m 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 "gabrielpickard/bgkit-350m" \ --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": "gabrielpickard/bgkit-350m", "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 "gabrielpickard/bgkit-350m" \ --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": "gabrielpickard/bgkit-350m", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use gabrielpickard/bgkit-350m with Docker Model Runner:
docker model run hf.co/gabrielpickard/bgkit-350m
bgkit-350m: merged encoder + decoder, compressor parts, standalone inference, model card
3149048 verified Download decoder/config.json from gabrielpickard/bgkit-350m: direct link, hf CLI and curl.
- Browser
- Download file 1.29 kB
-
https://huggingface.co/gabrielpickard/bgkit-350m/resolve/main/decoder/config.json
- Command line
-
hf download hf://gabrielpickard/bgkit-350m/decoder/config.json
-
curl -L -o config.json https://huggingface.co/gabrielpickard/bgkit-350m/resolve/main/decoder/config.json
1.29 kB
| { | |
| "architectures": [ | |
| "Lfm2ForCausalLM" | |
| ], | |
| "block_auto_adjust_ff_dim": true, | |
| "block_dim": 1024, | |
| "block_ffn_dim_multiplier": 1.0, | |
| "block_mlp_init_scale": 1.0, | |
| "block_multiple_of": 256, | |
| "block_norm_eps": 1e-05, | |
| "block_out_init_scale": 1.0, | |
| "block_use_swiglu": true, | |
| "block_use_xavier_init": true, | |
| "bos_token_id": 1, | |
| "conv_L_cache": 3, | |
| "conv_bias": false, | |
| "conv_dim": 1024, | |
| "conv_use_xavier_init": true, | |
| "dtype": "bfloat16", | |
| "eos_token_id": 7, | |
| "full_attn_idxs": null, | |
| "hidden_size": 1024, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 6656, | |
| "layer_types": [ | |
| "conv", | |
| "conv", | |
| "full_attention", | |
| "conv", | |
| "conv", | |
| "full_attention", | |
| "conv", | |
| "conv", | |
| "full_attention", | |
| "conv", | |
| "full_attention", | |
| "conv", | |
| "full_attention", | |
| "conv", | |
| "full_attention", | |
| "conv" | |
| ], | |
| "max_position_embeddings": 128000, | |
| "model_type": "lfm2", | |
| "norm_eps": 1e-05, | |
| "num_attention_heads": 16, | |
| "num_heads": 16, | |
| "num_hidden_layers": 16, | |
| "num_key_value_heads": 8, | |
| "pad_token_id": 0, | |
| "rope_parameters": { | |
| "rope_theta": 1000000.0, | |
| "rope_type": "default" | |
| }, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.5.4", | |
| "use_cache": false, | |
| "use_pos_enc": true, | |
| "vocab_size": 65536 | |
| } | |