Instructions to use Mathoctopus/Parallel_7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mathoctopus/Parallel_7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Mathoctopus/Parallel_7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Mathoctopus/Parallel_7B") model = AutoModelForCausalLM.from_pretrained("Mathoctopus/Parallel_7B") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Mathoctopus/Parallel_7B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Mathoctopus/Parallel_7B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Mathoctopus/Parallel_7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Mathoctopus/Parallel_7B
- SGLang
How to use Mathoctopus/Parallel_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 "Mathoctopus/Parallel_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": "Mathoctopus/Parallel_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 "Mathoctopus/Parallel_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": "Mathoctopus/Parallel_7B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Mathoctopus/Parallel_7B with Docker Model Runner:
docker model run hf.co/Mathoctopus/Parallel_7B
Update README.md
Browse files
README.md
CHANGED
|
@@ -1,5 +1,18 @@
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3 |
---
|
| 4 |
|
| 5 |
### Introduction
|
|
@@ -117,4 +130,4 @@ Or you can directly download them from
|
|
| 117 |
| MathOctupos<sup>C</sup>-33B | 53.7 | 51.5 |
|
| 118 |
|
| 119 |
## Intended Uses
|
| 120 |
-
These models are trained for research purposes. They are designed to solve multilingual math problems. They can be used in educational software, tutoring systems, or any application where a solution to a math problem is needed.
|
|
|
|
| 1 |
---
|
| 2 |
license: apache-2.0
|
| 3 |
+
datasets:
|
| 4 |
+
- Mathoctopus/GSM8KInstruct_Parallel
|
| 5 |
+
language:
|
| 6 |
+
- en
|
| 7 |
+
- es
|
| 8 |
+
- zh
|
| 9 |
+
- de
|
| 10 |
+
- ru
|
| 11 |
+
- th
|
| 12 |
+
- sw
|
| 13 |
+
- ja
|
| 14 |
+
- fr
|
| 15 |
+
- bn
|
| 16 |
---
|
| 17 |
|
| 18 |
### Introduction
|
|
|
|
| 130 |
| MathOctupos<sup>C</sup>-33B | 53.7 | 51.5 |
|
| 131 |
|
| 132 |
## Intended Uses
|
| 133 |
+
These models are trained for research purposes. They are designed to solve multilingual math problems. They can be used in educational software, tutoring systems, or any application where a solution to a math problem is needed.
|