Instructions to use macadeliccc/Laser-WestLake-2x7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use macadeliccc/Laser-WestLake-2x7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="macadeliccc/Laser-WestLake-2x7b")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("macadeliccc/Laser-WestLake-2x7b") model = AutoModelForMultimodalLM.from_pretrained("macadeliccc/Laser-WestLake-2x7b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use macadeliccc/Laser-WestLake-2x7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "macadeliccc/Laser-WestLake-2x7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "macadeliccc/Laser-WestLake-2x7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/macadeliccc/Laser-WestLake-2x7b
- SGLang
How to use macadeliccc/Laser-WestLake-2x7b 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 "macadeliccc/Laser-WestLake-2x7b" \ --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": "macadeliccc/Laser-WestLake-2x7b", "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 "macadeliccc/Laser-WestLake-2x7b" \ --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": "macadeliccc/Laser-WestLake-2x7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use macadeliccc/Laser-WestLake-2x7b with Docker Model Runner:
docker model run hf.co/macadeliccc/Laser-WestLake-2x7b
| license: apache-2.0 | |
| model-index: | |
| - name: Laser-WestLake-2x7b | |
| results: | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: AI2 Reasoning Challenge (25-Shot) | |
| type: ai2_arc | |
| config: ARC-Challenge | |
| split: test | |
| args: | |
| num_few_shot: 25 | |
| metrics: | |
| - type: acc_norm | |
| value: 72.27 | |
| name: normalized accuracy | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/Laser-WestLake-2x7b | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: HellaSwag (10-Shot) | |
| type: hellaswag | |
| split: validation | |
| args: | |
| num_few_shot: 10 | |
| metrics: | |
| - type: acc_norm | |
| value: 88.44 | |
| name: normalized accuracy | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/Laser-WestLake-2x7b | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: MMLU (5-Shot) | |
| type: cais/mmlu | |
| config: all | |
| split: test | |
| args: | |
| num_few_shot: 5 | |
| metrics: | |
| - type: acc | |
| value: 64.71 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/Laser-WestLake-2x7b | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: TruthfulQA (0-shot) | |
| type: truthful_qa | |
| config: multiple_choice | |
| split: validation | |
| args: | |
| num_few_shot: 0 | |
| metrics: | |
| - type: mc2 | |
| value: 69.25 | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/Laser-WestLake-2x7b | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: Winogrande (5-shot) | |
| type: winogrande | |
| config: winogrande_xl | |
| split: validation | |
| args: | |
| num_few_shot: 5 | |
| metrics: | |
| - type: acc | |
| value: 85.79 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/Laser-WestLake-2x7b | |
| name: Open LLM Leaderboard | |
| - task: | |
| type: text-generation | |
| name: Text Generation | |
| dataset: | |
| name: GSM8k (5-shot) | |
| type: gsm8k | |
| config: main | |
| split: test | |
| args: | |
| num_few_shot: 5 | |
| metrics: | |
| - type: acc | |
| value: 63.53 | |
| name: accuracy | |
| source: | |
| url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=macadeliccc/Laser-WestLake-2x7b | |
| name: Open LLM Leaderboard | |
| # Laser-Westlake-2x7B | |
|  | |
| This model is a moerge of [cognitivecomputations/WestLake-7B-v2-laser](https://huggingface.co/cognitivecomputations/WestLake-7B-v2-laser) and [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B) | |
| ## Process | |
| + WestLake-7B-v2-laser is the base model and one of the experts rather than utilizing 3 different models. | |
| + Will attempt to laser the final product as well, but given that the base has already been lasered it may not work out. | |
| + I have another version using the original, non-lasered WestLake-7B that I will also attempt to laser and report the differences. | |
| # Usage | |
| Usage is the same as the [original WestLake-7B](https://huggingface.co/senseable/WestLake-7B-v2) | |
| ## GGUF | |
| Available [here](https://huggingface.co/macadeliccc/Laser-WestLake-2x7b-GGUF) | |
| ## Evaluations | |
| <pre>----Benchmark Complete---- | |
| 2024-01-27 19:12:49 | |
| Time taken: 24.3 mins | |
| Prompt Format: ChatML | |
| Model: macadeliccc/Laser-WestLake-2x7b-GGUF | |
| Score (v2): 75.42 | |
| Parseable: 171.0 | |
| --------------- | |
| Batch completed | |
| Time taken: 24.4 mins | |
| --------------- | |
| </pre> | |
| # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) | |
| Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_macadeliccc__Laser-WestLake-2x7b) | |
| | Metric |Value| | |
| |---------------------------------|----:| | |
| |Avg. |74.00| | |
| |AI2 Reasoning Challenge (25-Shot)|72.27| | |
| |HellaSwag (10-Shot) |88.44| | |
| |MMLU (5-Shot) |64.71| | |
| |TruthfulQA (0-shot) |69.25| | |
| |Winogrande (5-shot) |85.79| | |
| |GSM8k (5-shot) |63.53| | |