Instructions to use uukuguy/speechless-tora-code-7b-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use uukuguy/speechless-tora-code-7b-v1.0 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="uukuguy/speechless-tora-code-7b-v1.0")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("uukuguy/speechless-tora-code-7b-v1.0")
model = AutoModelForCausalLM.from_pretrained("uukuguy/speechless-tora-code-7b-v1.0")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use uukuguy/speechless-tora-code-7b-v1.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "uukuguy/speechless-tora-code-7b-v1.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "uukuguy/speechless-tora-code-7b-v1.0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/uukuguy/speechless-tora-code-7b-v1.0

SGLang

How to use uukuguy/speechless-tora-code-7b-v1.0 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 "uukuguy/speechless-tora-code-7b-v1.0" \
    --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": "uukuguy/speechless-tora-code-7b-v1.0",
		"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 "uukuguy/speechless-tora-code-7b-v1.0" \
        --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": "uukuguy/speechless-tora-code-7b-v1.0",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use uukuguy/speechless-tora-code-7b-v1.0 with Docker Model Runner:
```
docker model run hf.co/uukuguy/speechless-tora-code-7b-v1.0
```

Update README.md

by cherry0328 - opened Jan 7

base: refs/heads/main

←

from: refs/pr/4

Discussion Files changed

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README.md +3 -1

README.md CHANGED Viewed

@@ -26,6 +26,8 @@ model-index:
       type: pass@1
       value: 51.829
       verified: false
 ---
 <p><h1> speechless-tora-code-7b-v1.0  </h1></p>
@@ -142,4 +144,4 @@ Detailed results can be found [here](https://huggingface.co/datasets/open-llm-le
 | TruthfulQA (0-shot)   | 42.06   |
 | Winogrande (5-shot)   | 62.9   |
 | GSM8K (5-shot)        | 0.91        |
-| DROP (3-shot)         | 28.48         |

       type: pass@1
       value: 51.829
       verified: false
+base_model:
+- llm-agents/tora-code-34b-v1.0
 ---
 <p><h1> speechless-tora-code-7b-v1.0  </h1></p>
 | TruthfulQA (0-shot)   | 42.06   |
 | Winogrande (5-shot)   | 62.9   |
 | GSM8K (5-shot)        | 0.91        |
+| DROP (3-shot)         | 28.48         |