Text Generation
Transformers
Safetensors
English
Chinese
qwen2
finance
text-generation-inference
conversational
Instructions to use IDEA-FinAI/TouchstoneGPT-7B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IDEA-FinAI/TouchstoneGPT-7B-Instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="IDEA-FinAI/TouchstoneGPT-7B-Instruct") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("IDEA-FinAI/TouchstoneGPT-7B-Instruct") model = AutoModelForCausalLM.from_pretrained("IDEA-FinAI/TouchstoneGPT-7B-Instruct", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use IDEA-FinAI/TouchstoneGPT-7B-Instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "IDEA-FinAI/TouchstoneGPT-7B-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": "IDEA-FinAI/TouchstoneGPT-7B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/IDEA-FinAI/TouchstoneGPT-7B-Instruct
- SGLang
How to use IDEA-FinAI/TouchstoneGPT-7B-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 "IDEA-FinAI/TouchstoneGPT-7B-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": "IDEA-FinAI/TouchstoneGPT-7B-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 "IDEA-FinAI/TouchstoneGPT-7B-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": "IDEA-FinAI/TouchstoneGPT-7B-Instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use IDEA-FinAI/TouchstoneGPT-7B-Instruct with Docker Model Runner:
docker model run hf.co/IDEA-FinAI/TouchstoneGPT-7B-Instruct
Commit History
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Update model card for Think-on-Graph 3.0 framework (RAG-Factory)
Verified signatureThis PR updates the model card for `IDEA-FinAI/TouchstoneGPT-7B-Instruct` to accurately reflect its association with the paper "[Think-on-Graph 3.0: Efficient and Adaptive LLM Reasoning on Heterogeneous Graphs via Multi-Agent Dual-Evolving Context Retrieval](https://huggingface.co/papers/2509.21710)" and the corresponding [RAG-Factory GitHub repository](https://github.com/DataArcTech/RAG-Factory). The update includes: - Clarifying that this repository hosts a `Qwen2-7B-Instruct` based model that can be used within the Think-on-Graph 3.0 framework. - Incorporating the abstract of the Think-on-Graph 3.0 paper. - Adding links to the paper and the RAG-Factory GitHub repository. - Integrating features, installation steps, and general usage examples from the RAG-Factory GitHub README to provide context for the framework. - Retaining the existing `transformers` sample usage for `TouchstoneGPT-7B-Instruct`, explicitly stating how to use this specific model. - Updating metadata with relevant t…c258334
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