Text Generation
Transformers
Safetensors
mistral
Merge
mergekit
lazymergekit
timpal0l/Mistral-7B-v0.1-flashback-v2
abacusai/Slerp-CM-mist-dpo
EmbeddedLLM/Mistral-7B-Merge-14-v0.2
text-generation-inference
Instructions to use FredrikBL/FlashbackMist-dare with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FredrikBL/FlashbackMist-dare with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FredrikBL/FlashbackMist-dare")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FredrikBL/FlashbackMist-dare") model = AutoModelForCausalLM.from_pretrained("FredrikBL/FlashbackMist-dare") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use FredrikBL/FlashbackMist-dare with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "FredrikBL/FlashbackMist-dare" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "FredrikBL/FlashbackMist-dare", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/FredrikBL/FlashbackMist-dare
- SGLang
How to use FredrikBL/FlashbackMist-dare 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 "FredrikBL/FlashbackMist-dare" \ --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": "FredrikBL/FlashbackMist-dare", "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 "FredrikBL/FlashbackMist-dare" \ --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": "FredrikBL/FlashbackMist-dare", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use FredrikBL/FlashbackMist-dare with Docker Model Runner:
docker model run hf.co/FredrikBL/FlashbackMist-dare
Update README.md
Browse files
README.md
CHANGED
|
@@ -10,6 +10,7 @@ base_model:
|
|
| 10 |
- timpal0l/Mistral-7B-v0.1-flashback-v2
|
| 11 |
- abacusai/Slerp-CM-mist-dpo
|
| 12 |
- EmbeddedLLM/Mistral-7B-Merge-14-v0.2
|
|
|
|
| 13 |
---
|
| 14 |
|
| 15 |
# test-dare
|
|
|
|
| 10 |
- timpal0l/Mistral-7B-v0.1-flashback-v2
|
| 11 |
- abacusai/Slerp-CM-mist-dpo
|
| 12 |
- EmbeddedLLM/Mistral-7B-Merge-14-v0.2
|
| 13 |
+
license: apache-2.0
|
| 14 |
---
|
| 15 |
|
| 16 |
# test-dare
|