Instructions to use jeiku/Bones_3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jeiku/Bones_3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jeiku/Bones_3B", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("jeiku/Bones_3B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use jeiku/Bones_3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jeiku/Bones_3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jeiku/Bones_3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jeiku/Bones_3B
- SGLang
How to use jeiku/Bones_3B 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 "jeiku/Bones_3B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jeiku/Bones_3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "jeiku/Bones_3B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jeiku/Bones_3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use jeiku/Bones_3B with Docker Model Runner:
docker model run hf.co/jeiku/Bones_3B
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Download README.md from jeiku/Bones_3B: direct link, hf CLI and curl.
- Browser
- Download file 1.14 kB
-
https://huggingface.co/jeiku/Bones_3B/resolve/main/README.md
- Command line
-
hf download hf://jeiku/Bones_3B/README.md
-
curl -L -o README.md https://huggingface.co/jeiku/Bones_3B/resolve/main/README.md
1.14 kB
| base_model: | |
| - cxllin/StableHermes-3b | |
| - jondurbin/airoboros-3b-3p0 | |
| - jeiku/Rosa_v1_3B | |
| tags: | |
| - mergekit | |
| - merge | |
| # great | |
| This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). | |
| ## Merge Details | |
| ### Merge Method | |
| This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [jeiku/Rosa_v1_3B](https://huggingface.co/jeiku/Rosa_v1_3B) as a base. | |
| ### Models Merged | |
| The following models were included in the merge: | |
| * [cxllin/StableHermes-3b](https://huggingface.co/cxllin/StableHermes-3b) | |
| * [jondurbin/airoboros-3b-3p0](https://huggingface.co/jondurbin/airoboros-3b-3p0) | |
| ### Configuration | |
| The following YAML configuration was used to produce this model: | |
| ```yaml | |
| models: | |
| - model: cxllin/StableHermes-3b | |
| parameters: | |
| weight: 0.33 | |
| density: 1 | |
| - model: jondurbin/airoboros-3b-3p0 | |
| parameters: | |
| weight: 0.33 | |
| density: 1 | |
| - model: jeiku/Rosa_v1_3B | |
| parameters: | |
| weight: 0.33 | |
| density: 1 | |
| merge_method: dare_ties | |
| base_model: jeiku/Rosa_v1_3B | |
| parameters: | |
| dtype: bfloat16 | |
| ``` | |