|
--- |
|
language: |
|
- en |
|
- fr |
|
- de |
|
- es |
|
- it |
|
- pt |
|
- zh |
|
- ja |
|
- ru |
|
- ko |
|
license: other |
|
license_name: mrl |
|
inference: false |
|
license_link: https://mistral.ai/licenses/MRL-0.1.md |
|
base_model: |
|
- mistralai/Ministral-8B-Instruct-2410 |
|
--- |
|
|
|
## Installation |
|
|
|
To use this model, install the required packages: |
|
|
|
```bash |
|
pip install -U mistral-common transformers torch |
|
``` |
|
|
|
## Usage Example |
|
|
|
Here's a Python script demonstrating how to use the model for chat completion: |
|
|
|
```python |
|
import torch |
|
from pathlib import Path |
|
from transformers import AutoModelForCausalLM |
|
from mistral_common.tokens.tokenizers.mistral import MistralTokenizer |
|
from mistral_common.tokens.tokenizers.tekken import SpecialTokenPolicy |
|
from mistral_common.protocol.instruct.messages import UserMessage |
|
from mistral_common.protocol.instruct.request import ChatCompletionRequest |
|
from huggingface_hub import snapshot_download |
|
|
|
def get_model_path(path_or_hf_repo: str, revision: str = None) -> Path: |
|
"""Ensures the model is available locally, downloading if necessary.""" |
|
model_path = Path(path_or_hf_repo) |
|
if not model_path.exists(): |
|
model_path = Path( |
|
snapshot_download( |
|
repo_id=path_or_hf_repo, |
|
revision=revision, |
|
allow_patterns=[ |
|
"*.json", |
|
"*.safetensors", |
|
"*.py", |
|
"tokenizer.model", |
|
"*.tiktoken", |
|
"*.txt", |
|
], |
|
resume_download=True, |
|
) |
|
) |
|
return model_path |
|
|
|
def load_chat_request(message: str) -> ChatCompletionRequest: |
|
"""Creates a chat completion request with a user message.""" |
|
return ChatCompletionRequest(messages=[UserMessage(content=message)]) |
|
|
|
# Model setup |
|
model_name = "prince-canuma/Ministral-8B-Instruct-2410-HF" |
|
model = AutoModelForCausalLM.from_pretrained(model_name, device_map="auto") |
|
model_path = get_model_path(model_name) |
|
|
|
tokenizer = MistralTokenizer.from_file(f"{model_path}/tokenizer.json") |
|
tekken = tokenizer.instruct_tokenizer.tokenizer |
|
tekken.special_token_policy = SpecialTokenPolicy.IGNORE |
|
|
|
# Chat interaction |
|
user_message = "Tell me a short story about a robot learning to paint." |
|
completion_request = load_chat_request(user_message) |
|
tokens = tokenizer.encode_chat_completion(completion_request).tokens |
|
input_ids = torch.tensor(tokens).unsqueeze(0) |
|
|
|
# Generate response |
|
output = model.generate(input_ids, max_new_tokens=500, temperature=0.7, do_sample=True) |
|
response = tokenizer.decode(output[0][input_ids.shape[1]:].tolist()) |
|
|
|
print("User:", user_message) |
|
print("Model:", response) |
|
|
|
``` |
|
|
|
## Model Details |
|
|
|
- **Developed by:** Mistral AI |
|
- **Model type:** Causal Language Model |
|
- **Language(s):** English |
|
- **License:** [mrl](https://mistral.ai/licenses/MRL-0.1.md) |
|
- **Resources for more information:** |
|
- [Model Repository](https://huggingface.co/prince-canuma/Ministral-8B-Instruct-2410-HF) |
|
- [Mistral AI GitHub](https://github.com/mistralai) |
