Instructions to use IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct
- SGLang
How to use IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct 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 "IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct" \ --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": "IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct", "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 "IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct" \ --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": "IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct with Docker Model Runner:
docker model run hf.co/IQuestLab/IQuest-Coder-V1-40B-Loop-Instruct
update transformer version
Browse files- config.json +1 -1
- generation_config.json +1 -1
config.json
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"loop_num": 2,
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"loop_window_size": 64,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.
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"auto_map": {
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"AutoConfig": "configuration_iquestloopcoder.IQuestLoopCoderConfig",
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"AutoModel": "modeling_iquestloopcoder.IQuestLoopCoderModel",
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"loop_num": 2,
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"loop_window_size": 64,
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"torch_dtype": "bfloat16",
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+
"transformers_version": "4.56.0",
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"auto_map": {
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"AutoConfig": "configuration_iquestloopcoder.IQuestLoopCoderConfig",
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"AutoModel": "modeling_iquestloopcoder.IQuestLoopCoderModel",
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generation_config.json
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": [2, 75864, 75869],
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"transformers_version": "4.
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}
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"_from_model_config": true,
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"bos_token_id": 1,
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"eos_token_id": [2, 75864, 75869],
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"transformers_version": "4.56.0"
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}
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