Text Generation
Transformers
Safetensors
mistral
Merge
mergekit
lazymergekit
mlabonne/NeuralBeagle14-7B
FelixChao/WestSeverus-7B-DPO-v2
jsfs11/TurdusTrixBeagle-DARETIES-7B
text-generation-inference
Instructions to use CultriX/CombinaTrix-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CultriX/CombinaTrix-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CultriX/CombinaTrix-7B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CultriX/CombinaTrix-7B") model = AutoModelForCausalLM.from_pretrained("CultriX/CombinaTrix-7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use CultriX/CombinaTrix-7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CultriX/CombinaTrix-7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CultriX/CombinaTrix-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CultriX/CombinaTrix-7B
- SGLang
How to use CultriX/CombinaTrix-7B 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 "CultriX/CombinaTrix-7B" \ --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": "CultriX/CombinaTrix-7B", "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 "CultriX/CombinaTrix-7B" \ --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": "CultriX/CombinaTrix-7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CultriX/CombinaTrix-7B with Docker Model Runner:
docker model run hf.co/CultriX/CombinaTrix-7B
Update README.md
Browse files
README.md
CHANGED
|
@@ -13,6 +13,10 @@ base_model:
|
|
| 13 |
license: apache-2.0
|
| 14 |
---
|
| 15 |
|
|
|
|
|
|
|
|
|
|
|
|
|
| 16 |
# CombinaTrix-7B
|
| 17 |
|
| 18 |
CombinaTrix-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
|
|
|
|
| 13 |
license: apache-2.0
|
| 14 |
---
|
| 15 |
|
| 16 |
+
# EDIT:
|
| 17 |
+
Always check my space for the latest benchmark results for my models!
|
| 18 |
+
* https://huggingface.co/spaces/CultriX/Yet_Another_LLM_Leaderboard
|
| 19 |
+
|
| 20 |
# CombinaTrix-7B
|
| 21 |
|
| 22 |
CombinaTrix-7B is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
|