Text Generation
Transformers
Safetensors
English
mistral
conversational
custom_code
text-generation-inference
Instructions to use adalbertojunior/DUSMistral with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use adalbertojunior/DUSMistral with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="adalbertojunior/DUSMistral", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("adalbertojunior/DUSMistral", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("adalbertojunior/DUSMistral", trust_remote_code=True, device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use adalbertojunior/DUSMistral with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "adalbertojunior/DUSMistral" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "adalbertojunior/DUSMistral", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/adalbertojunior/DUSMistral
- SGLang
How to use adalbertojunior/DUSMistral 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 "adalbertojunior/DUSMistral" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "adalbertojunior/DUSMistral", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "adalbertojunior/DUSMistral" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "adalbertojunior/DUSMistral", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use adalbertojunior/DUSMistral with Docker Model Runner:
docker model run hf.co/adalbertojunior/DUSMistral
Download config.json from adalbertojunior/DUSMistral: direct link, hf CLI and curl.
- Browser
- Download file 994 Bytes
-
https://huggingface.co/adalbertojunior/DUSMistral/resolve/main/config.json
- Command line
-
hf download hf://adalbertojunior/DUSMistral/config.json
-
curl -L -o config.json https://huggingface.co/adalbertojunior/DUSMistral/resolve/main/config.json
994 Bytes
| { | |
| "_name_or_path": "models/dusmistral-dolphin/checkpoint-400", | |
| "architectures": [ | |
| "DusMistralForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_dusmistral.DusMistralConfig", | |
| "AutoModel": "modeling_dusmistral.DusMistralModel", | |
| "AutoModelForCausalLM": "modeling_dusmistral.DusMistralForCausalLM" | |
| }, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "hidden_act": "silu", | |
| "hidden_size": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 14336, | |
| "layer_order": [ | |
| [ | |
| 0, | |
| 24 | |
| ], | |
| [ | |
| 8, | |
| 32 | |
| ] | |
| ], | |
| "max_position_embeddings": 32768, | |
| "model_type": "mistral", | |
| "num_attention_heads": 32, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 8, | |
| "rms_norm_eps": 1e-06, | |
| "rope_theta": 10000.0, | |
| "sliding_window": 4096, | |
| "tie_word_embeddings": false, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.39.0.dev0", | |
| "unsloth_version": "2024.3", | |
| "use_cache": false, | |
| "vocab_size": 32001 | |
| } | |