Instructions to use jeiku/longtest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jeiku/longtest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="jeiku/longtest", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("jeiku/longtest", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use jeiku/longtest with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jeiku/longtest" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jeiku/longtest", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/jeiku/longtest
- SGLang
How to use jeiku/longtest 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 "jeiku/longtest" \ --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": "jeiku/longtest", "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 "jeiku/longtest" \ --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": "jeiku/longtest", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use jeiku/longtest with Docker Model Runner:
docker model run hf.co/jeiku/longtest
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base_model:
- jeiku/Rosa_v1_3B
- jeiku/ToxicNoRobotsRosaHermesBoros_3B
tags:
- mergekit
- merge
---
# long
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 passthrough merge method.
### Models Merged
The following models were included in the merge:
* [jeiku/Rosa_v1_3B](https://huggingface.co/jeiku/Rosa_v1_3B)
* [jeiku/ToxicNoRobotsRosaHermesBoros_3B](https://huggingface.co/jeiku/ToxicNoRobotsRosaHermesBoros_3B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: jeiku/Rosa_v1_3B
layer_range: [0, 10]
- sources:
- model: jeiku/ToxicNoRobotsRosaHermesBoros_3B
layer_range: [8, 18]
- sources:
- model: jeiku/Rosa_v1_3B
layer_range: [16, 26]
- sources:
- model: jeiku/ToxicNoRobotsRosaHermesBoros_3B
layer_range: [22, 32]
merge_method: passthrough
dtype: float16
```
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