初始化项目，由ModelHub XC社区提供模型
Model: aixonlab/Grey-12b Source: Original Platform
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README.md
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README.md
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---
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base_model: aixonlab/Aether-12b
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language:
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- en
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license: apache-2.0
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tags:
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- text-generation-inference
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- transformers
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- mistral
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---
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<img src="https://cdn-uploads.huggingface.co/production/uploads/66dcee3321f901b049f48002/jWXtbknuetFdz5fkFn-ey.png" width="800"/>
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# Grey-12b
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Grey-12b is a merged language model created by combining multiple models using the della_linear merge method, with Aether-12b as the base model.
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## Model Details 📊
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- Developed by: AIXON Lab
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- Model type: Merged Causal Language Model
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- Language(s): English (primarily), may support other languages
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- License: apache-2.0
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- Repository: https://huggingface.co/aixonlab/Grey-12b
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## Model Architecture 🏗️
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- Base model: aixonlab/Aether-12b
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- Parameter count: ~12 billion
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- Architecture specifics: Transformer-based language model
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- Merge method: della_linear
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### Merged Models
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1. VAGOsolutions/SauerkrautLM-Nemo-12b-Instruct
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- Weight: 0.33
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- Density: 0.4
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2. cognitivecomputations/dolphin-2.9.3-mistral-nemo-12b
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- Weight: 0.77
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- Density: 0.8
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## Technical Specifications
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- Dtype: float16
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- Tokenizer source: base (aixonlab/Aether-12b)
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- Merge parameters:
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- Epsilon: 0.05
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- Lambda: 1
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## Intended Use 🎯
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As an advanced language model for various natural language processing tasks, including but not limited to text generation, question-answering, and analysis.
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## Ethical Considerations 🤔
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As a merged model based on multiple sources, Grey-12b may inherit biases and limitations from its constituent models. Users should be aware of potential biases in generated content and use the model responsibly.
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## Performance and Evaluation
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Performance metrics and evaluation results for Grey-12b are yet to be determined. Users are encouraged to contribute their findings and benchmarks.
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## Limitations and Biases
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The model may exhibit biases present in its training data and constituent models. It's crucial to critically evaluate the model's outputs and use them in conjunction with human judgment.
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## Additional Information
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For more details on the base model and constituent models, please refer to their respective model cards and documentation.
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## Acknowledgments 🙏
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We acknowledge the contributions of:
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- VAGOsolutions for the SauerkrautLM-Nemo-12b-Instruct model
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- Cognitive Computations for the dolphin-2.9.3-mistral-nemo-12b model
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## How to Use
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model = AutoModelForCausalLM.from_pretrained("aixonlab/Grey-12b")
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tokenizer = AutoTokenizer.from_pretrained("aixonlab/Grey-12b")
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prompt = "Once upon a time"
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input_ids = tokenizer(prompt, return_tensors="pt").input_ids
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generated_ids = model.generate(input_ids, max_length=100)
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generated_text = tokenizer.decode(generated_ids, skip_special_tokens=True)
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print(generated_text)
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config.json
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{
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"_name_or_path": "./models/12b-merged",
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"architectures": [
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"MistralForCausalLM"
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],
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"eos_token_id": 2,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"rope_scaling": null,
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"rope_theta": 1000000.0,
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"sliding_window": null,
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"tie_word_embeddings": false,
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"torch_dtype": "float16",
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"transformers_version": "4.45.1",
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"unsloth_version": "2024.9.post2",
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"use_cache": true,
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"vocab_size": 131072
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}
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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}
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30
special_tokens_map.json
Normal file
30
special_tokens_map.json
Normal file
@@ -0,0 +1,30 @@
|
||||
{
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||||
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}
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||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
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||||
oid sha256:b0240ce510f08e6c2041724e9043e33be9d251d1e4a4d94eb68cd47b954b61d2
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size 17078292
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8015
tokenizer_config.json
Normal file
8015
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user