Text Generation
Transformers
Safetensors
qwen2
mergekit
Merge
conversational
text-generation-inference
Instructions to use Upcycle-AI/Codeus-7B-Pre-Alpha with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Upcycle-AI/Codeus-7B-Pre-Alpha with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Upcycle-AI/Codeus-7B-Pre-Alpha") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Upcycle-AI/Codeus-7B-Pre-Alpha") model = AutoModelForMultimodalLM.from_pretrained("Upcycle-AI/Codeus-7B-Pre-Alpha") 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=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Upcycle-AI/Codeus-7B-Pre-Alpha with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Upcycle-AI/Codeus-7B-Pre-Alpha" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Upcycle-AI/Codeus-7B-Pre-Alpha", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Upcycle-AI/Codeus-7B-Pre-Alpha
- SGLang
How to use Upcycle-AI/Codeus-7B-Pre-Alpha 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 "Upcycle-AI/Codeus-7B-Pre-Alpha" \ --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": "Upcycle-AI/Codeus-7B-Pre-Alpha", "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 "Upcycle-AI/Codeus-7B-Pre-Alpha" \ --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": "Upcycle-AI/Codeus-7B-Pre-Alpha", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Upcycle-AI/Codeus-7B-Pre-Alpha with Docker Model Runner:
docker model run hf.co/Upcycle-AI/Codeus-7B-Pre-Alpha
| base_model: | |
| - Qwen/Qwen2.5-Coder-7B | |
| - microsoft/NextCoder-7B | |
| - TIGER-Lab/VisCoder2-7B | |
| - DeepHat/DeepHat-V1-7B | |
| - open-r1/OlympicCoder-7B | |
| library_name: transformers | |
| tags: | |
| - mergekit | |
| - merge | |
| # merged_super_mario | |
| 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 TIES](https://arxiv.org/abs/2311.03099) merge method using [Qwen/Qwen2.5-Coder-7B](https://huggingface.co/Qwen/Qwen2.5-Coder-7B) as a base. | |
| ### Models Merged | |
| The following models were included in the merge: | |
| * [microsoft/NextCoder-7B](https://huggingface.co/microsoft/NextCoder-7B) | |
| * [TIGER-Lab/VisCoder2-7B](https://huggingface.co/TIGER-Lab/VisCoder2-7B) | |
| * [DeepHat/DeepHat-V1-7B](https://huggingface.co/DeepHat/DeepHat-V1-7B) | |
| * [open-r1/OlympicCoder-7B](https://huggingface.co/open-r1/OlympicCoder-7B) | |
| ### Configuration | |
| The following YAML configuration was used to produce this model: | |
| ```yaml | |
| models: | |
| - model: open-r1/OlympicCoder-7B | |
| parameters: | |
| density: 0.3 | |
| weight: 0.35 | |
| - model: microsoft/NextCoder-7B | |
| parameters: | |
| density: 0.25 | |
| weight: 0.3 | |
| - model: TIGER-Lab/VisCoder2-7B | |
| parameters: | |
| density: 0.25 | |
| weight: 0.3 | |
| - model: DeepHat/DeepHat-V1-7B | |
| parameters: | |
| density: 0.2 | |
| weight: 0.2 | |
| merge_method: dare_ties | |
| base_model: Qwen/Qwen2.5-Coder-7B | |
| parameters: | |
| int8_mask: true | |
| dtype: bfloat16 | |
| tokenizer_source: base | |
| ``` | |