Instructions to use gywy/Mistral-7B-v0.1-chinese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gywy/Mistral-7B-v0.1-chinese with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="gywy/Mistral-7B-v0.1-chinese")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gywy/Mistral-7B-v0.1-chinese")
model = AutoModelForCausalLM.from_pretrained("gywy/Mistral-7B-v0.1-chinese", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use gywy/Mistral-7B-v0.1-chinese with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gywy/Mistral-7B-v0.1-chinese"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "gywy/Mistral-7B-v0.1-chinese",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/gywy/Mistral-7B-v0.1-chinese

SGLang

How to use gywy/Mistral-7B-v0.1-chinese 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 "gywy/Mistral-7B-v0.1-chinese" \
    --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": "gywy/Mistral-7B-v0.1-chinese",
		"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 "gywy/Mistral-7B-v0.1-chinese" \
        --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": "gywy/Mistral-7B-v0.1-chinese",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use gywy/Mistral-7B-v0.1-chinese with Docker Model Runner:
```
docker model run hf.co/gywy/Mistral-7B-v0.1-chinese
```

Mistral-7B-v0.1-chinese / tokenizer_config.json

eggqq007

Upload 9 files

b0bd3af almost 3 years ago

Raw

History Blame Contribute Delete

3.79 kB

	{
	"add_bos_token": true,
	"add_eos_token": false,
	"added_tokens_decoder": {
	"0": {
	"content": "<unk>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"1": {
	"content": "<s>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"2": {
	"content": "</s>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"48593": {
	"content": "[UNUSED1]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48594": {
	"content": "[UNUSED2]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48595": {
	"content": "[UNUSED3]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48596": {
	"content": "[UNUSED4]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48597": {
	"content": "[UNUSED5]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48598": {
	"content": "[UNUSED6]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48599": {
	"content": "[UNUSED7]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48600": {
	"content": "[UNUSED8]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48601": {
	"content": "[UNUSED9]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48602": {
	"content": "[UNUSED10]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48603": {
	"content": "[UNUSED11]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48604": {
	"content": "[UNUSED12]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48605": {
	"content": "[UNUSED13]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48606": {
	"content": "[UNUSED14]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"48607": {
	"content": "[UNUSED15]",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": false
	}
	},
	"additional_special_tokens": [
	"<unk>",
	"<s>",
	"</s>"
	],
	"bos_token": "<s>",
	"clean_up_tokenization_spaces": false,
	"eos_token": "</s>",
	"legacy": true,
	"model_max_length": 1000000000000000019884624838656,
	"pad_token": "</s>",
	"sp_model_kwargs": {},
	"spaces_between_special_tokens": false,
	"tokenizer_class": "LlamaTokenizer",
	"tokenizer_file": null,
	"trust_remote_code": false,
	"unk_token": "<unk>",
	"use_default_system_prompt": true,
	"use_fast": true
	}