Upload Llama-3-13B-Instruct-v0.1.Q4_K_S.gguf with huggingface_hub
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ai-modelscope
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README.md
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README.md
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---
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license: Apache License 2.0
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#model-type:
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##如 gpt、phi、llama、chatglm、baichuan 等
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#- gpt
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base_model: "meta-llama/Meta-Llama-3-8B-Instruct"
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library_name: transformers
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tags:
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- mergekit
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- merge
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- facebook
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- meta
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- pytorch
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- llama
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- llama-3
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language:
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- en
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pipeline_tag: text-generation
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license: other
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license_name: llama3
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license_link: LICENSE
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inference: false
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model_creator: MaziyarPanahi
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model_name: Llama-3-13B-Instruct-v0.1
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quantized_by: MaziyarPanahi
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#domain:
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##如 nlp、cv、audio、multi-modal
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#- nlp
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#language:
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##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
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#- cn
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#metrics:
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##如 CIDEr、Blue、ROUGE 等
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#- CIDEr
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#tags:
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##各种自定义，包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
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#- pretrained
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#tools:
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##如 vllm、fastchat、llamacpp、AdaSeq 等
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#- vllm
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---
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### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重，可浏览“模型文件”页面获取。
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#### 您可以通过如下git clone命令，或者ModelScope SDK来下载模型
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SDK下载
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```bash
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#安装ModelScope
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pip install modelscope
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```
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# QuantFactory/Llama-3-13B-Instruct-v0.1-GGUF
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This is quantized version of [MaziyarPanahi/Llama-3-13B-Instruct-v0.1](https://huggingface.co/MaziyarPanahi/Llama-3-13B-Instruct-v0.1) created using llama.cpp
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# Original Model Card
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<img src="./llama-3-merges.webp" alt="Goku 8x22B v0.1 Logo" width="500" style="margin-left:'auto' margin-right:'auto' display:'block'"/>
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# Llama-3-13B-Instruct-v0.1
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This model is a self-merge of `meta-llama/Meta-Llama-3-8B-Instruct` model.
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# How to use
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You can use this model by using `MaziyarPanahi/Llama-3-13B-Instruct-v0.1` as the model name in Hugging Face's
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transformers library.
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```python
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#SDK模型下载
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from modelscope import snapshot_download
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model_dir = snapshot_download('QuantFactory/Llama-3-13B-Instruct-v0.1-GGUF')
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```
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Git下载
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```
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#Git模型下载
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git clone https://www.modelscope.cn/QuantFactory/Llama-3-13B-Instruct-v0.1-GGUF.git
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from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
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from transformers import pipeline
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import torch
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model_id = "MaziyarPanahi/Llama-3-13B-Instruct-v0.1"
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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device_map="auto",
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trust_remote_code=True,
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# attn_implementation="flash_attention_2"
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)
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tokenizer = AutoTokenizer.from_pretrained(
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model_id,
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trust_remote_code=True
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)
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streamer = TextStreamer(tokenizer)
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pipeline = pipeline(
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"text-generation",
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model=model,
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tokenizer=tokenizer,
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model_kwargs={"torch_dtype": torch.bfloat16},
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streamer=streamer
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)
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# Then you can use the pipeline to generate text.
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messages = [
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{"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
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{"role": "user", "content": "Who are you?"},
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]
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prompt = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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terminators = [
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tokenizer.eos_token_id,
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tokenizer.convert_tokens_to_ids("<|eot_id|>")
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]
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outputs = pipeline(
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prompt,
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max_new_tokens=256,
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eos_token_id=terminators,
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do_sample=True,
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temperature=0.6,
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top_p=0.95,
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)
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print(outputs[0]["generated_text"][len(prompt):])
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```
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<p style="color: lightgrey;">如果您是本模型的贡献者，我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>，及时完善模型卡片内容。</p>
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## Prompt template
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```text
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<|begin_of_text|><|start_header_id|>system<|end_header_id|>
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You are a helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|>
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what's 25-4*2+3<|eot_id|><|start_header_id|>assistant<|end_header_id|>
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To evaluate this expression, we need to follow the order of operations (PEMDAS):
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1. First, multiply 4 and 2: 4*2 = 8
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2. Then, subtract 8 from 25: 25 - 8 = 17
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3. Finally, add 3: 17 + 3 = 20
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So, 25-4*2+3 = 20!<|eot_id|>
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To evaluate this expression, we need to follow the order of operations (PEMDAS):
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1. First, multiply 4 and 2: 4*2 = 8
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2. Then, subtract 8 from 25: 25 - 8 = 17
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3. Finally, add 3: 17 + 3 = 20
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So, 25-4*2+3 = 20!
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```
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