M4-ai/TinyMistral-6x248M
1
0
Fork 0
Code Issues Pull Requests Actions Projects Releases Wiki Activity

初始化项目，由ModelHub XC社区提供模型

Browse Source 
Model: M4-ai/TinyMistral-6x248M
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-09-30 23:04:53 +08:00
commit 7c789ad62d
9 changed files with 91605 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

35
.gitattributes vendored Normal file
View File

@@ -0,0 +1,35 @@
*.7z filter=lfs diff=lfs merge=lfs -text
*.arrow filter=lfs diff=lfs merge=lfs -text
*.bin filter=lfs diff=lfs merge=lfs -text
*.bz2 filter=lfs diff=lfs merge=lfs -text
*.ckpt filter=lfs diff=lfs merge=lfs -text
*.ftz filter=lfs diff=lfs merge=lfs -text
*.gz filter=lfs diff=lfs merge=lfs -text
*.h5 filter=lfs diff=lfs merge=lfs -text
*.joblib filter=lfs diff=lfs merge=lfs -text
*.lfs.* filter=lfs diff=lfs merge=lfs -text
*.mlmodel filter=lfs diff=lfs merge=lfs -text
*.model filter=lfs diff=lfs merge=lfs -text
*.msgpack filter=lfs diff=lfs merge=lfs -text
*.npy filter=lfs diff=lfs merge=lfs -text
*.npz filter=lfs diff=lfs merge=lfs -text
*.onnx filter=lfs diff=lfs merge=lfs -text
*.ot filter=lfs diff=lfs merge=lfs -text
*.parquet filter=lfs diff=lfs merge=lfs -text
*.pb filter=lfs diff=lfs merge=lfs -text
*.pickle filter=lfs diff=lfs merge=lfs -text
*.pkl filter=lfs diff=lfs merge=lfs -text
*.pt filter=lfs diff=lfs merge=lfs -text
*.pth filter=lfs diff=lfs merge=lfs -text
*.rar filter=lfs diff=lfs merge=lfs -text
*.safetensors filter=lfs diff=lfs merge=lfs -text
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
*.tar.* filter=lfs diff=lfs merge=lfs -text
*.tar filter=lfs diff=lfs merge=lfs -text
*.tflite filter=lfs diff=lfs merge=lfs -text
*.tgz filter=lfs diff=lfs merge=lfs -text
*.wasm filter=lfs diff=lfs merge=lfs -text
*.xz filter=lfs diff=lfs merge=lfs -text
*.zip filter=lfs diff=lfs merge=lfs -text
*.zst filter=lfs diff=lfs merge=lfs -text
*tfevents* filter=lfs diff=lfs merge=lfs -text

167
README.md Normal file
View File

@@ -0,0 +1,167 @@
---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- Locutusque/TinyMistral-248M-v2
- Locutusque/TinyMistral-248M-v2.5
- Locutusque/TinyMistral-248M-v2.5-Instruct
- jtatman/tinymistral-v2-pycoder-instruct-248m
- Felladrin/TinyMistral-248M-SFT-v4
- Locutusque/TinyMistral-248M-v2-Instruct
base_model:
- Locutusque/TinyMistral-248M-v2
- Locutusque/TinyMistral-248M-v2.5
- Locutusque/TinyMistral-248M-v2.5-Instruct
- jtatman/tinymistral-v2-pycoder-instruct-248m
- Felladrin/TinyMistral-248M-SFT-v4
- Locutusque/TinyMistral-248M-v2-Instruct
inference:
parameters:
do_sample: true
temperature: 0.2
top_p: 0.14
top_k: 12
max_new_tokens: 250
repetition_penalty: 1.15
widget:
- text: |
<|im_start|>user
Write me a Python program that calculates the factorial of n. <|im_end|>
<|im_start|>assistant
- text: >-
An emerging clinical approach to treat substance abuse disorders involves a
form of cognitive-behavioral therapy whereby addicts learn to reduce their
reactivity to drug-paired stimuli through cue-exposure or extinction
training. It is, however,
datasets:
- nampdn-ai/mini-peS2o
---
# TinyMistral-6x248M
TinyMistral-6x248M is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [Locutusque/TinyMistral-248M-v2](https://huggingface.co/Locutusque/TinyMistral-248M-v2)
* [Locutusque/TinyMistral-248M-v2.5](https://huggingface.co/Locutusque/TinyMistral-248M-v2.5)
* [Locutusque/TinyMistral-248M-v2.5-Instruct](https://huggingface.co/Locutusque/TinyMistral-248M-v2.5-Instruct)
* [jtatman/tinymistral-v2-pycoder-instruct-248m](https://huggingface.co/jtatman/tinymistral-v2-pycoder-instruct-248m)
* [Felladrin/TinyMistral-248M-SFT-v4](https://huggingface.co/Felladrin/TinyMistral-248M-SFT-v4)
* [Locutusque/TinyMistral-248M-v2-Instruct](https://huggingface.co/Locutusque/TinyMistral-248M-v2-Instruct)
The resulting model is then pre-trained on 600,000 examples of nampdn-ai/mini-peS2o.
We don't recommend using the Inference API as the model has serious performance degradation.
### Recommended inference parameters
```
do_sample: true
temperature: 0.2
top_p: 0.14
top_k: 12
repetition_penalty: 1.15
```
## 🧩 Configuration
```yaml
base_model: Locutusque/TinyMistral-248M-v2.5
experts:
- source_model: Locutusque/TinyMistral-248M-v2
positive_prompts:
- "An emerging trend in global economics is"
- "TITLE: The Next Generation of Internet Connectivity"
- "begin a comprehensive analysis on the sociopolitical effects of"
negative_prompts:
- "Code a simple"
- "Explain the Krebs cycle in detail"
- "Compose a sonnet about"
- source_model: Locutusque/TinyMistral-248M-v2.5
positive_prompts:
- "Advanced C++ memory management techniques"
- "C# asynchronous programming best practices"
- "AI's role in predictive analytics"
- "textbook review on machine learning algorithms"
- "## Exercise: Design a C# interface for a CRM system"
- "## Solution: Optimize an AI-powered recommendation engine"
negative_prompts:
- "Narrate the story of"
- "The ethical considerations in"
- "Review the latest art exhibition by"
- source_model: Locutusque/TinyMistral-248M-v2.5-Instruct
positive_prompts:
- "What is the chemical formula for photosynthesis?"
- "Identification of a new mineral found on Mars"
- "physics: Explaining the concept of relativity"
- "Solve for x using differential equations:"
- "history: Analyze the causes of the French Revolution"
negative_prompts:
- "Devise a business plan for"
- "The evolution of culinary arts"
- "Orchestrate a piece for a string quartet"
- source_model: jtatman/tinymistral-v2-pycoder-instruct-248m
positive_prompts:
- "Write a Python program for facial recognition"
- "Explain dynamic typing in programming languages"
- "algorithm development for efficient data sorting"
negative_prompts:
- "Who was the first Emperor of Rome?"
- "Discuss the political dynamics in"
- "Provide a proof for Fermat's Last Theorem"
- "physics: The principles of thermodynamics"
- source_model: Felladrin/TinyMistral-248M-SFT-v4
positive_prompts:
- "Escreba sobre a influência da música no Brasil"
- "Voici un guide pour les voyageurs en France"
- "Para entender la política de México, se debe considerar"
- "Cuales son los efectos de la globalización en Argentina"
- "Welche gesellschaftlichen Veränderungen gibt es in Deutschland"
- "If you had to imagine a utopian city, what would be its core values?"
negative_prompts:
- "Calculate the integral of"
- "Describe the process of cell division"
- "Review the latest advancements in quantum computing"
- source_model: Locutusque/TinyMistral-248M-v2-Instruct
positive_prompts:
- "Write an essay on the evolution of international trade laws"
- "What are the key components of a sustainable urban ecosystem?"
- "instruct on effective negotiation techniques in diplomacy"
- "How does cognitive bias affect decision making in high-pressure environments?"
- "Identify the architectural significance of the Sydney Opera House"
negative_prompts:
- "Develop a script to automate"
- "Understanding inheritance in object-oriented programming"
- "philosophy of existentialism in contemporary society"
```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "M4-ai/TinyMistral-6x248M"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)
messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```

30
config.json Normal file
View File

@@ -0,0 +1,30 @@
{
"_name_or_path": "/media/sebastian/T7/Projects/saved_models",
"architectures": [
"MixtralForCausalLM"
],
"attention_dropout": 0.0,
"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 1024,
"initializer_range": 0.02,
"intermediate_size": 4096,
"max_position_embeddings": 32768,
"model_type": "mixtral",
"num_attention_heads": 32,
"num_experts_per_tok": 2,
"num_hidden_layers": 12,
"num_key_value_heads": 8,
"num_local_experts": 6,
"output_router_logits": false,
"rms_norm_eps": 1e-06,
"rope_theta": 10000.0,
"router_aux_loss_coef": 0.001,
"sliding_window": null,
"tie_word_embeddings": false,
"torch_dtype": "float32",
"transformers_version": "4.36.2",
"use_cache": true,
"vocab_size": 32005
}

6
generation_config.json Normal file
View File

@@ -0,0 +1,6 @@
{
"_from_model_config": true,
"bos_token_id": 1,
"eos_token_id": 2,
"transformers_version": "4.36.2"
}

73
mergekit_moe_config.yml Normal file
View File

@@ -0,0 +1,73 @@
base_model: Locutusque/TinyMistral-248M-v2.5
experts:
- source_model: Locutusque/TinyMistral-248M-v2
positive_prompts:
- "An emerging trend in global economics is"
- "TITLE: The Next Generation of Internet Connectivity"
- "begin a comprehensive analysis on the sociopolitical effects of"
negative_prompts:
- "Code a simple"
- "Explain the Krebs cycle in detail"
- "Compose a sonnet about"
- source_model: Locutusque/TinyMistral-248M-v2.5
positive_prompts:
- "Advanced C++ memory management techniques"
- "C# asynchronous programming best practices"
- "AI's role in predictive analytics"
- "textbook review on machine learning algorithms"
- "## Exercise: Design a C# interface for a CRM system"
- "## Solution: Optimize an AI-powered recommendation engine"
negative_prompts:
- "Narrate the story of"
- "The ethical considerations in"
- "Review the latest art exhibition by"
- source_model: Locutusque/TinyMistral-248M-v2.5-Instruct
positive_prompts:
- "What is the chemical formula for photosynthesis?"
- "Identification of a new mineral found on Mars"
- "physics: Explaining the concept of relativity"
- "Solve for x using differential equations:"
- "history: Analyze the causes of the French Revolution"
negative_prompts:
- "Devise a business plan for"
- "The evolution of culinary arts"
- "Orchestrate a piece for a string quartet"
- source_model: jtatman/tinymistral-v2-pycoder-instruct-248m
positive_prompts:
- "Write a Python program for facial recognition"
- "Explain dynamic typing in programming languages"
- "algorithm development for efficient data sorting"
negative_prompts:
- "Who was the first Emperor of Rome?"
- "Discuss the political dynamics in"
- "Provide a proof for Fermat's Last Theorem"
- "physics: The principles of thermodynamics"
- source_model: Felladrin/TinyMistral-248M-SFT-v4
positive_prompts:
- "Escreba sobre a influência da música no Brasil"
- "Voici un guide pour les voyageurs en France"
- "Para entender la política de México, se debe considerar"
- "Cuales son los efectos de la globalización en Argentina"
- "Welche gesellschaftlichen Veränderungen gibt es in Deutschland"
- "If you had to imagine a utopian city, what would be its core values?"
negative_prompts:
- "Calculate the integral of"
- "Describe the process of cell division"
- "Review the latest advancements in quantum computing"
- source_model: Locutusque/TinyMistral-248M-v2-Instruct
positive_prompts:
- "Write an essay on the evolution of international trade laws"
- "What are the key components of a sustainable urban ecosystem?"
- "instruct on effective negotiation techniques in diplomacy"
- "How does cognitive bias affect decision making in high-pressure environments?"
- "Identify the architectural significance of the Sydney Opera House"
negative_prompts:
- "Develop a script to automate"
- "Understanding inheritance in object-oriented programming"
- "philosophy of existentialism in contemporary society"

3
model.safetensors Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:643390caf77542ac81aa6756dc908473226f383fe59a7b5eeab8f085bf0a551b
size 4012327872

30
special_tokens_map.json Normal file
View File

@@ -0,0 +1,30 @@
{
"bos_token": {
"content": "<|bos|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"eos_token": {
"content": "<|endoftext|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"pad_token": {
"content": "<|bos|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
},
"unk_token": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false
}
}

91172
tokenizer.json Normal file
View File

File diff suppressed because it is too large Load Diff

89
tokenizer_config.json Normal file
View File

@@ -0,0 +1,89 @@
{
"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
},
"32000": {
"content": "<|bos|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"32001": {
"content": "<|endoftext|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"32002": {
"content": "[PAD]",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"32003": {
"content": "<|ASSISTANT|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"32004": {
"content": "<|USER|>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"additional_special_tokens": [],
"bos_token": "<|bos|>",
"clean_up_tokenization_spaces": false,
"eos_token": "<|endoftext|>",
"legacy": true,
"max_length": 1536,
"model_max_length": 1000000000000000019884624838656,
"pad_to_multiple_of": null,
"pad_token": "<|bos|>",
"pad_token_type_id": 0,
"padding_side": "right",
"sp_model_kwargs": {},
"spaces_between_special_tokens": false,
"stride": 0,
"tokenizer_class": "LlamaTokenizer",
"truncation_side": "right",
"truncation_strategy": "longest_first",
"unk_token": "<unk>",
"use_default_system_prompt": true
}