初始化项目，由ModelHub XC社区提供模型
Model: Vlor999/mlx-UNfilteredAI-1B Source: Original Platform
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README.md
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---
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license: mit
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language:
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- en
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tags:
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- UnfilteredAI
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- mlx
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library_name: mlx
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base_model: UnfilteredAI/UNfilteredAI-1B
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pipeline_tag: text-generation
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---
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# MLX UnfilteredAI-1B Model Card
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This is the MLX version of the UnfilteredAI-1B model, optimized for efficient inference on Apple Silicon devices using Apple's MLX framework.
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## Model Details
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### Model Description
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The MLX UnfilteredAI-1B is a converted version of the original UnfilteredAI-1B text generation model, adapted for Apple's MLX machine learning framework. This allows for fast and efficient text generation on macOS devices with M-series chips, leveraging the native capabilities of Apple Silicon.
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- **Developed by:** UnfilteredAI
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- **Model type:** Text generation language model
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- **Language(s) (NLP):** English (primary), supports other languages
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- **License:** MIT
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- **Base model:** UnfilteredAI/UNfilteredAI-1B
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### Model Sources
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- **Repository:** https://huggingface.co/UnfilteredAI/UNfilteredAI-1B
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- **MLX Conversion:** This repository
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## Uses
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### Direct Use
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This model can be used for text generation tasks such as:
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- Creative writing
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- Conversational AI
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- Educational and research applications
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- Content generation without traditional filters
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### Out-of-Scope Use
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The model is uncensored and may generate sensitive, controversial, or harmful content. It should not be used for:
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- Generating illegal or unethical content
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- Misinformation or propaganda
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- Any applications requiring content moderation
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## Bias, Risks, and Limitations
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As an uncensored model, it may exhibit biases present in the training data and generate inappropriate content. Users should be aware of potential risks including:
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- Generation of biased or offensive text
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- Potential for misuse in harmful applications
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- Inconsistencies in output quality
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### Recommendations
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Use responsibly and with caution. Implement appropriate safeguards if deploying in production environments.
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## How to Get Started with the Model
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To use this model, you'll need to install the MLX library and mlx-lm:
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```bash
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# uv version
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uv init .
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uv add mlx mlx-lm
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# pip version
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pip install mlx mlx-lm
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```
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Then, load and use the model:
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```python
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from mlx_lm import load, generate
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# Load the model from hugging-face
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model, tokenizer = load("Vlor999/mlx-UNfilteredAI-1B")
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# Generate text
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prompt = "Hello, how are you?"
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response = generate(model, tokenizer, prompt, max_tokens=100, verbose=True)
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print(response)
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```
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Then run the model:
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```bash
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uv run python filename.py
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# or by using the environment
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source .venv/bin/activate
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python filename.py
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```
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Or directly using mlx-lm:
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```bash
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uv run mlx_lm.chat --model Vlor999/mlx-UNfilteredAI-1B
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# Example:
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uv run mlx_lm.chat --model Vlor999/mlx-UNfilteredAI-1B --max-tokens=4096
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# to have more informations about how to use mlx_lm you can run:
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uv run mlx_lm.chat --help
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```
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config.json
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||||
}
|
||||
}
|
||||
277129
tokenizer.json
Normal file
277129
tokenizer.json
Normal file
File diff suppressed because it is too large
Load Diff
16
tokenizer_config.json
Normal file
16
tokenizer_config.json
Normal file
@@ -0,0 +1,16 @@
|
||||
{
|
||||
"add_prefix_space": null,
|
||||
"additional_special_tokens": null,
|
||||
"backend": "tokenizers",
|
||||
"bos_token": "<s>",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "</s>",
|
||||
"is_local": true,
|
||||
"model_max_length": 2048,
|
||||
"pad_token": "</s>",
|
||||
"padding_side": "right",
|
||||
"sp_model_kwargs": {},
|
||||
"tokenizer_class": "LlamaTokenizer",
|
||||
"unk_token": "<unk>",
|
||||
"use_default_system_prompt": false
|
||||
}
|
||||
Reference in New Issue
Block a user