Instructions to use flopsy1/mistral-7B-arXflix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flopsy1/mistral-7B-arXflix with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="flopsy1/mistral-7B-arXflix")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("flopsy1/mistral-7B-arXflix", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use flopsy1/mistral-7B-arXflix with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "flopsy1/mistral-7B-arXflix" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "flopsy1/mistral-7B-arXflix", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/flopsy1/mistral-7B-arXflix
- SGLang
How to use flopsy1/mistral-7B-arXflix 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 "flopsy1/mistral-7B-arXflix" \ --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": "flopsy1/mistral-7B-arXflix", "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 "flopsy1/mistral-7B-arXflix" \ --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": "flopsy1/mistral-7B-arXflix", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use flopsy1/mistral-7B-arXflix with Docker Model Runner:
docker model run hf.co/flopsy1/mistral-7B-arXflix
Mistral 7B instruct finetuned to produce script for axflix
Load model directly
from mistral_inference.model import Transformer
from mistral_inference.generate import generate
from mistral_common.tokens.tokenizers.mistral import MistralTokenizer
from mistral_common.protocol.instruct.messages import UserMessage
from mistral_common.protocol.instruct.request import ChatCompletionRequest
tokenizer = MistralTokenizer.from_file("tokenizer.model.v3") # change to extracted tokenizer file
model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.3") # change to extracted model dir
model.load_lora("lora.safetensors")
- Downloads last month
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Model tree for flopsy1/mistral-7B-arXflix
Base model
mistralai/Mistral-7B-v0.3 Finetuned
mistralai/Mistral-7B-Instruct-v0.3