Instructions to use TJUNLP/FuxiTranyu-8B-DPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TJUNLP/FuxiTranyu-8B-DPO with Transformers:

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

pipe = pipeline("text-generation", model="TJUNLP/FuxiTranyu-8B-DPO", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("TJUNLP/FuxiTranyu-8B-DPO", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TJUNLP/FuxiTranyu-8B-DPO with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/TJUNLP/FuxiTranyu-8B-DPO

SGLang

How to use TJUNLP/FuxiTranyu-8B-DPO 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 "TJUNLP/FuxiTranyu-8B-DPO" \
    --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": "TJUNLP/FuxiTranyu-8B-DPO",
		"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 "TJUNLP/FuxiTranyu-8B-DPO" \
        --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": "TJUNLP/FuxiTranyu-8B-DPO",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TJUNLP/FuxiTranyu-8B-DPO with Docker Model Runner:
```
docker model run hf.co/TJUNLP/FuxiTranyu-8B-DPO
```

rrjin commited on Oct 23, 2024

Commit

7283cfd

verified ·

1 Parent(s): 601213b

Upload config.json with huggingface_hub

Browse files

Files changed (1) hide show

config.json +7 -8

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "/data1/hrsun/FuxiTranyu-8B-Chat",
   "activation_function": "gelu_fast",
   "architectures": [
     "FuxiTranyuForCausalLM"
@@ -10,8 +10,8 @@
     "AutoConfig": "configuration_fuxitranyu.FuxiTranyuConfig",
     "AutoModelForCausalLM": "modeling_fuxitranyu.FuxiTranyuForCausalLM"
   },
-  "bos_token_id": 250680,
-  "eos_token_id": 250681,
   "hidden_size": 4096,
   "initializer_range": 0.01,
   "intermediate_size": 16384,
@@ -20,15 +20,14 @@
   "num_attention_heads": 32,
   "num_hidden_layers": 30,
   "num_key_value_heads": 32,
-  "pad_token_id": 250681,
   "pretraining_tp": 1,
   "rms_norm_eps": 1e-05,
   "rope_scaling": null,
   "rope_theta": 10000.0,
   "tie_word_embeddings": false,
   "tokenizer_class": "GPT2TokenizerFast",
-  "torch_dtype": "float16",
-  "transformers_version": "4.42.4",
-  "use_cache": true,
-  "vocab_size": 250682
 }

 {
+  "_name_or_path": "/home/s2022244109/rrjin/trl_data/checkpoint/sft_002/checkpoint-3963",
   "activation_function": "gelu_fast",
   "architectures": [
     "FuxiTranyuForCausalLM"
     "AutoConfig": "configuration_fuxitranyu.FuxiTranyuConfig",
     "AutoModelForCausalLM": "modeling_fuxitranyu.FuxiTranyuForCausalLM"
   },
+  "bos_token_id": 0,
+  "eos_token_id": 0,
   "hidden_size": 4096,
   "initializer_range": 0.01,
   "intermediate_size": 16384,
   "num_attention_heads": 32,
   "num_hidden_layers": 30,
   "num_key_value_heads": 32,
   "pretraining_tp": 1,
   "rms_norm_eps": 1e-05,
   "rope_scaling": null,
   "rope_theta": 10000.0,
   "tie_word_embeddings": false,
   "tokenizer_class": "GPT2TokenizerFast",
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.44.2",
+  "use_cache": false,
+  "vocab_size": 250680
 }