Instructions to use CompassioninMachineLearning/Instructllama_plus1kmedaiGrok with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CompassioninMachineLearning/Instructllama_plus1kmedaiGrok with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CompassioninMachineLearning/Instructllama_plus1kmedaiGrok")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CompassioninMachineLearning/Instructllama_plus1kmedaiGrok") model = AutoModelForCausalLM.from_pretrained("CompassioninMachineLearning/Instructllama_plus1kmedaiGrok") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use CompassioninMachineLearning/Instructllama_plus1kmedaiGrok with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CompassioninMachineLearning/Instructllama_plus1kmedaiGrok" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CompassioninMachineLearning/Instructllama_plus1kmedaiGrok", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CompassioninMachineLearning/Instructllama_plus1kmedaiGrok
- SGLang
How to use CompassioninMachineLearning/Instructllama_plus1kmedaiGrok 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 "CompassioninMachineLearning/Instructllama_plus1kmedaiGrok" \ --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": "CompassioninMachineLearning/Instructllama_plus1kmedaiGrok", "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 "CompassioninMachineLearning/Instructllama_plus1kmedaiGrok" \ --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": "CompassioninMachineLearning/Instructllama_plus1kmedaiGrok", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Unsloth Studio new
How to use CompassioninMachineLearning/Instructllama_plus1kmedaiGrok with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CompassioninMachineLearning/Instructllama_plus1kmedaiGrok to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for CompassioninMachineLearning/Instructllama_plus1kmedaiGrok to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for CompassioninMachineLearning/Instructllama_plus1kmedaiGrok to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="CompassioninMachineLearning/Instructllama_plus1kmedaiGrok", max_seq_length=2048, ) - Docker Model Runner
How to use CompassioninMachineLearning/Instructllama_plus1kmedaiGrok with Docker Model Runner:
docker model run hf.co/CompassioninMachineLearning/Instructllama_plus1kmedaiGrok
(Trained with Unsloth)
Browse files- config.json +2 -2
config.json
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id":
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.55.4",
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"unsloth_fixed": true,
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"unsloth_version": "2025.
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"use_cache": true,
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"vocab_size": 128256
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}
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": 128009,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.55.4",
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"unsloth_fixed": true,
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"unsloth_version": "2025.10.10",
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"use_cache": true,
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"vocab_size": 128256
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}
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