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
IQuest-Coder-V1-40B-Instruct权重问题
#18 opened 4 months ago
by
zhangjiaqing
8 tps on nVidia H200
5
#17 opened 4 months ago
by
svilen333
🎉 llama.cpp Support Now Available!
🔥🚀 4
3
#16 opened 4 months ago
by
nologik
IQuest-Coder-V1
#15 opened 4 months ago
by
AlphaOrionis9527
Using "IQuest-Coder-V1-40B-Loop-Instruct" on Cursor
2
#14 opened 4 months ago
by
Maub69
What vLLM version should I use to deploy this model?
3
#13 opened 4 months ago
by
yyg201708
Benchmaxxed
🧠👍 10
2
#12 opened 4 months ago
by
Tom-Neverwinter
Availability of 7B and 14B models mentioned in the paper
👀 3
1
#11 opened 4 months ago
by
Sopelllka
need official fp8 weights
#7 opened 4 months ago
by
wangruiai2023
LM Studio Support with Q4_K_S please?
❤️ 3
1
#6 opened 5 months ago
by
Cagannn
这又是谁家高手了?!
🤗 1
1
#3 opened 5 months ago
by
shangyue2333
smaller + thinking models
👀👍 15
#2 opened 5 months ago
by
Fizzarolli
can you share benchmarks for all models you released
#1 opened 5 months ago
by
Narutoouz