a4e409ab13
Model: MaziyarPanahi/neural-chat-7b-v3-2-Mistral-7B-Instruct-v0.1 Source: Original Platform
83 lines
1.8 KiB
Markdown
83 lines
1.8 KiB
Markdown
---
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license: apache-2.0
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tags:
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- Safetensors
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- mistral
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- text-generation-inference
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- merge
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- mistral
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- 7b
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- mistralai/Mistral-7B-Instruct-v0.1
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- Intel/neural-chat-7b-v3-2
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- transformers
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- pytorch
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- mistral
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- text-generation
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- LLMs
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- math
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- Intel
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- en
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- dataset:meta-math/MetaMathQA
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- arxiv:2309.12284
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- license:apache-2.0
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- model-index
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- autotrain_compatible
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- endpoints_compatible
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- has_space
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- text-generation-inference
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- region:us
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---
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# neural-chat-7b-v3-2-Mistral-7B-Instruct-v0.1
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neural-chat-7b-v3-2-Mistral-7B-Instruct-v0.1 is a merge of the following models:
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* [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)
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* [Intel/neural-chat-7b-v3-2](https://huggingface.co/Intel/neural-chat-7b-v3-2)
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## 🧩 Configuration
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```yaml
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slices:
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- sources:
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- model: mistralai/Mistral-7B-Instruct-v0.1
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layer_range: [0, 32]
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- model: Intel/neural-chat-7b-v3-2
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layer_range: [0, 32]
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merge_method: slerp
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base_model: mistralai/Mistral-7B-Instruct-v0.1
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parameters:
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t:
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- filter: self_attn
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value: [0, 0.5, 0.3, 0.7, 1]
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- filter: mlp
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value: [1, 0.5, 0.7, 0.3, 0]
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- value: 0.5
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dtype: bfloat16
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```
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "MaziyarPanahi/neural-chat-7b-v3-2-Mistral-7B-Instruct-v0.1"
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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``` |