Image-Text-to-Text
Transformers
English
mistral
pixtral
vlm
multimodal
orbital-mechanics
hohmann-transfer-orbits
Instructions to use Taylor658/Titan-Hohmann with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taylor658/Titan-Hohmann with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Taylor658/Titan-Hohmann")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Taylor658/Titan-Hohmann", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Taylor658/Titan-Hohmann with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Taylor658/Titan-Hohmann" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Taylor658/Titan-Hohmann", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Taylor658/Titan-Hohmann
- SGLang
How to use Taylor658/Titan-Hohmann 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 "Taylor658/Titan-Hohmann" \ --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": "Taylor658/Titan-Hohmann", "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 "Taylor658/Titan-Hohmann" \ --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": "Taylor658/Titan-Hohmann", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Taylor658/Titan-Hohmann with Docker Model Runner:
docker model run hf.co/Taylor658/Titan-Hohmann
Update README.md
#2
by Taylor658 - opened
README.md
CHANGED
|
@@ -5,21 +5,21 @@ datasets:
|
|
| 5 |
language:
|
| 6 |
- en
|
| 7 |
base_model:
|
| 8 |
-
- mistralai/
|
| 9 |
---
|
| 10 |
|
| 11 |
-
# Mistral
|
| 12 |
|
| 13 |
## Model Card
|
| 14 |
|
| 15 |
### Model Overview
|
| 16 |
|
| 17 |
-
**Model Name**: `mistral-
|
| 18 |
**Model Type**: Transformer-based language model
|
| 19 |
**Languages**: English
|
| 20 |
**License**: Apache License 2.0
|
| 21 |
|
| 22 |
-
This model is based on the **Mistral
|
| 23 |
|
| 24 |
---
|
| 25 |
|
|
@@ -27,7 +27,7 @@ This model is based on the **Mistral 8B** foundation model and is being fine-tun
|
|
| 27 |
|
| 28 |
- **Developers**: A Taylor
|
| 29 |
- **Model Architecture**: Transformer-based with enhancements for code generation and multimodal processing
|
| 30 |
-
- **Parameters**:
|
| 31 |
- **Native Function Calling**: Supported
|
| 32 |
- **Multimodal Capabilities**: Text and image processing
|
| 33 |
|
|
@@ -117,4 +117,4 @@ The model is currently being fine tuned to enhance its capabilities in handling
|
|
| 117 |
- **Email**
|
| 118 |
- **Repository**: https://github.com/ATaylorAerospace/HohmannHET
|
| 119 |
|
| 120 |
-
---
|
|
|
|
| 5 |
language:
|
| 6 |
- en
|
| 7 |
base_model:
|
| 8 |
+
- mistralai/Mistral-7B-Instruct-v0.3
|
| 9 |
---
|
| 10 |
|
| 11 |
+
# Mistral 7B Fine-Tuned on Titan-Hohmann-Transfer-Orbit Dataset
|
| 12 |
|
| 13 |
## Model Card
|
| 14 |
|
| 15 |
### Model Overview
|
| 16 |
|
| 17 |
+
**Model Name**: `mistral-7b-titan-hohmann`
|
| 18 |
**Model Type**: Transformer-based language model
|
| 19 |
**Languages**: English
|
| 20 |
**License**: Apache License 2.0
|
| 21 |
|
| 22 |
+
This model is based on the **Mistral-7B-Instruct-v0.3** foundation model and is being fine-tuned on the **titan-hohmann-transfer-orbit** dataset. It is designed to assist with advanced orbital calculations, specifically focusing on space probe Hohmann transfer orbits, and includes support for native function calling and multimodal inputs.
|
| 23 |
|
| 24 |
---
|
| 25 |
|
|
|
|
| 27 |
|
| 28 |
- **Developers**: A Taylor
|
| 29 |
- **Model Architecture**: Transformer-based with enhancements for code generation and multimodal processing
|
| 30 |
+
- **Parameters**: 7 Billion
|
| 31 |
- **Native Function Calling**: Supported
|
| 32 |
- **Multimodal Capabilities**: Text and image processing
|
| 33 |
|
|
|
|
| 117 |
- **Email**
|
| 118 |
- **Repository**: https://github.com/ATaylorAerospace/HohmannHET
|
| 119 |
|
| 120 |
+
---
|