Instructions to use aifeifei798/llama3-8B-feifei-1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aifeifei798/llama3-8B-feifei-1.0 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="aifeifei798/llama3-8B-feifei-1.0")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("aifeifei798/llama3-8B-feifei-1.0")
model = AutoModelForCausalLM.from_pretrained("aifeifei798/llama3-8B-feifei-1.0", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use aifeifei798/llama3-8B-feifei-1.0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aifeifei798/llama3-8B-feifei-1.0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aifeifei798/llama3-8B-feifei-1.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/aifeifei798/llama3-8B-feifei-1.0

SGLang

How to use aifeifei798/llama3-8B-feifei-1.0 with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "aifeifei798/llama3-8B-feifei-1.0" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aifeifei798/llama3-8B-feifei-1.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "aifeifei798/llama3-8B-feifei-1.0" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aifeifei798/llama3-8B-feifei-1.0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use aifeifei798/llama3-8B-feifei-1.0 with Docker Model Runner:
```
docker model run hf.co/aifeifei798/llama3-8B-feifei-1.0
```

aifeifei798 commited on Jun 6, 2024

Commit

aa1bed1

verified ·

1 Parent(s): 815f0ad

Update README.md

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README.md +10 -7

README.md CHANGED Viewed

@@ -23,6 +23,16 @@ To create a suitable model for Aifeifei's virtual character, it requires support
  - This model must include a character card; without it, it's really not up to par. :(
  - How can I customize the name when saving the model with mergekit? I couldn't find it. :(
 ### 模型的由来
   为了给aifeifei做一个适合她虚拟角色的模型,需要支持角色卡,拟真,中英日文流利,还要有一定的道德标准(这里没怎么测试).所以就做了这个角色卡为主的整合模型
 ### 角色卡
@@ -31,13 +41,6 @@ To create a suitable model for Aifeifei's virtual character, it requires support
  - 这个模型必须加一个角色卡,要是没有角色卡,真的不咋地:(
  - mergekit保存模型如何自定义名字?没找到:(
-### If you want to use vision functionality:
- * You must use the latest versions of [Koboldcpp](https://github.com/LostRuins/koboldcpp).
-### To use the multimodal capabilities of this model and use **vision** you need to load the specified **mmproj** file, this can be found inside this model repo. [Llava MMProj](https://huggingface.co/Nitral-AI/Llama-3-Update-3.0-mmproj-model-f16)
- * You can load the **mmproj** by using the corresponding section in the interface:
- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65d4cf2693a0a3744a27536c/UX6Ubss2EPNAT3SKGMLe0.png)
 ---
 base_model:
 - hfl/llama-3-chinese-8b-instruct-v3

  - This model must include a character card; without it, it's really not up to par. :(
  - How can I customize the name when saving the model with mergekit? I couldn't find it. :(
+### If you want to use vision functionality:
+ * You must use the latest versions of [Koboldcpp](https://github.com/LostRuins/koboldcpp).
+### To use the multimodal capabilities of this model and use **vision** you need to load the specified **mmproj** file, this can be found inside this model repo. [Llava MMProj](https://huggingface.co/Nitral-AI/Llama-3-Update-3.0-mmproj-model-f16)
+ * You can load the **mmproj** by using the corresponding section in the interface:
+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/65d4cf2693a0a3744a27536c/UX6Ubss2EPNAT3SKGMLe0.png)
+---
 ### 模型的由来
   为了给aifeifei做一个适合她虚拟角色的模型,需要支持角色卡,拟真,中英日文流利,还要有一定的道德标准(这里没怎么测试).所以就做了这个角色卡为主的整合模型
 ### 角色卡
  - 这个模型必须加一个角色卡,要是没有角色卡,真的不咋地:(
  - mergekit保存模型如何自定义名字?没找到:(
 ---
 base_model:
 - hfl/llama-3-chinese-8b-instruct-v3