Text Generation
Transformers
Safetensors
mistral
Mistral_Star
Mistral_Quiet
Mistral
Mixtral
Question-Answer
Token-Classification
Sequence-Classification
SpydazWeb-AI
chemistry
biology
legal
code
climate
medical
text-generation-inference
custom_code
Instructions to use LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project
- SGLang
How to use LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project 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 "LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project" \ --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": "LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project", "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 "LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project" \ --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": "LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project with Docker Model Runner:
docker model run hf.co/LeroyDyer/_Spydaz_Web_AI_MistralStar_001_Project
Upload folder using huggingface_hub
Browse files- config.json +4 -4
- generation_config.json +2 -2
- model-00001-of-00003.safetensors +3 -0
- model-00002-of-00003.safetensors +3 -0
- model-00003-of-00003.safetensors +3 -0
- model.safetensors.index.json +0 -0
- tokenizer.json +1 -6
config.json
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{
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"_name_or_path": "LeroyDyer/
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"architectures": [
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"MistralStarForCausalLM"
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],
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"attention_dropout": 0.0,
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"auto_map": {
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"AutoConfig": "LeroyDyer/
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"AutoModel": "LeroyDyer/
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"AutoModelForCausalLM": "LeroyDyer/
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},
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"bos_token_id": 1,
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"eos_token_id": 2,
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{
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"_name_or_path": "LeroyDyer/_Spydaz_Web_AI_V2_Aligned",
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"architectures": [
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"MistralStarForCausalLM"
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],
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"attention_dropout": 0.0,
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"auto_map": {
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"AutoConfig": "LeroyDyer/_Spydaz_Web_AI_V2_Aligned--SpydazWebAI_Mistral_Transformer.MistralConfig",
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"AutoModel": "LeroyDyer/_Spydaz_Web_AI_V2_Aligned--SpydazWebAI_Mistral_Transformer.MistralModel",
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"AutoModelForCausalLM": "LeroyDyer/_Spydaz_Web_AI_V2_Aligned--SpydazWebAI_Mistral_Transformer.MistralStarForCausalLM"
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},
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"bos_token_id": 1,
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"eos_token_id": 2,
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generation_config.json
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"eos_token_id": 2,
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"num_beams": 4,
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"num_return_sequences": 2,
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"temperature": 0.
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"top_k":
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"top_p": 0.68,
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"transformers_version": "4.42.4",
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"use_cache": false
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"eos_token_id": 2,
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"num_beams": 4,
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"num_return_sequences": 2,
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"temperature": 0.7,
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"top_k": 100,
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"top_p": 0.68,
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"transformers_version": "4.42.4",
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"use_cache": false
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version https://git-lfs.github.com/spec/v1
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size 4943211664
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size 4999819336
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size 4641221080
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model.safetensors.index.json
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tokenizer.json
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