Instructions to use tanliboy/lambda-llama-3-8b-dpo-test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tanliboy/lambda-llama-3-8b-dpo-test with Transformers:

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

pipe = pipeline("text-generation", model="tanliboy/lambda-llama-3-8b-dpo-test")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("tanliboy/lambda-llama-3-8b-dpo-test")
model = AutoModelForCausalLM.from_pretrained("tanliboy/lambda-llama-3-8b-dpo-test", 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 tanliboy/lambda-llama-3-8b-dpo-test with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "tanliboy/lambda-llama-3-8b-dpo-test"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "tanliboy/lambda-llama-3-8b-dpo-test",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/tanliboy/lambda-llama-3-8b-dpo-test

SGLang

How to use tanliboy/lambda-llama-3-8b-dpo-test 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 "tanliboy/lambda-llama-3-8b-dpo-test" \
    --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": "tanliboy/lambda-llama-3-8b-dpo-test",
		"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 "tanliboy/lambda-llama-3-8b-dpo-test" \
        --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": "tanliboy/lambda-llama-3-8b-dpo-test",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use tanliboy/lambda-llama-3-8b-dpo-test with Docker Model Runner:
```
docker model run hf.co/tanliboy/lambda-llama-3-8b-dpo-test
```

tanliboy commited on Sep 18, 2024

Commit

a320a9a

verified ·

1 Parent(s): b7cb8bf

End of training

Browse files

Files changed (5) hide show

README.md +15 -9
all_results.json +13 -0
config.json +1 -1
eval_results.json +16 -0
runs/Sep18_05-34-48_action-graph-trainer/events.out.tfevents.1726645681.action-graph-trainer.2590949.1 +3 -0

README.md CHANGED Viewed

@@ -3,9 +3,15 @@ library_name: transformers
 license: llama3.1
 base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
 tags:
 - trl
 - dpo
 - generated_from_trainer
 model-index:
 - name: lambda-llama-3-8b-dpo-test
   results: []
@@ -16,17 +22,17 @@ should probably proofread and complete it, then remove this comment. -->
 # lambda-llama-3-8b-dpo-test
-This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5776
-- Rewards/chosen: -1.0426
-- Rewards/rejected: -1.6196
 - Rewards/accuracies: 0.7063
-- Rewards/margins: 0.5769
-- Logps/rejected: -557.9310
-- Logps/chosen: -509.0269
-- Logits/rejected: -2.6060
-- Logits/chosen: -2.4454
 ## Model description

 license: llama3.1
 base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
 tags:
+- alignment-handbook
 - trl
 - dpo
 - generated_from_trainer
+- trl
+- dpo
+- generated_from_trainer
+datasets:
+- HuggingFaceH4/ultrafeedback_binarized
 model-index:
 - name: lambda-llama-3-8b-dpo-test
   results: []
 # lambda-llama-3-8b-dpo-test
+This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the HuggingFaceH4/ultrafeedback_binarized dataset.
 It achieves the following results on the evaluation set:
+- Loss: 0.5772
+- Rewards/chosen: -1.0430
+- Rewards/rejected: -1.6270
 - Rewards/accuracies: 0.7063
+- Rewards/margins: 0.5841
+- Logps/rejected: -558.6804
+- Logps/chosen: -509.0577
+- Logits/rejected: -2.5324
+- Logits/chosen: -2.3779
 ## Model description

all_results.json CHANGED Viewed

@@ -1,5 +1,18 @@
 {
     "epoch": 0.9984301412872841,
     "total_flos": 0.0,
     "train_loss": 0.6095632167232361,
     "train_runtime": 6900.3625,

 {
     "epoch": 0.9984301412872841,
+    "eval_logits/chosen": -2.3779289722442627,
+    "eval_logits/rejected": -2.5323691368103027,
+    "eval_logps/chosen": -509.05767822265625,
+    "eval_logps/rejected": -558.6803588867188,
+    "eval_loss": 0.577161967754364,
+    "eval_rewards/accuracies": 0.7063491940498352,
+    "eval_rewards/chosen": -1.0429552793502808,
+    "eval_rewards/margins": 0.5840887427330017,
+    "eval_rewards/rejected": -1.6270442008972168,
+    "eval_runtime": 88.0288,
+    "eval_samples": 2000,
+    "eval_samples_per_second": 22.72,
+    "eval_steps_per_second": 0.716,
     "total_flos": 0.0,
     "train_loss": 0.6095632167232361,
     "train_runtime": 6900.3625,

config.json CHANGED Viewed

@@ -34,6 +34,6 @@
   "tie_word_embeddings": false,
   "torch_dtype": "bfloat16",
   "transformers_version": "4.44.2",
-  "use_cache": false,
   "vocab_size": 128256
 }

   "tie_word_embeddings": false,
   "torch_dtype": "bfloat16",
   "transformers_version": "4.44.2",
+  "use_cache": true,
   "vocab_size": 128256
 }

eval_results.json ADDED Viewed

	@@ -0,0 +1,16 @@

+{
+    "epoch": 0.9984301412872841,
+    "eval_logits/chosen": -2.3779289722442627,
+    "eval_logits/rejected": -2.5323691368103027,
+    "eval_logps/chosen": -509.05767822265625,
+    "eval_logps/rejected": -558.6803588867188,
+    "eval_loss": 0.577161967754364,
+    "eval_rewards/accuracies": 0.7063491940498352,
+    "eval_rewards/chosen": -1.0429552793502808,
+    "eval_rewards/margins": 0.5840887427330017,
+    "eval_rewards/rejected": -1.6270442008972168,
+    "eval_runtime": 88.0288,
+    "eval_samples": 2000,
+    "eval_samples_per_second": 22.72,
+    "eval_steps_per_second": 0.716
+}

runs/Sep18_05-34-48_action-graph-trainer/events.out.tfevents.1726645681.action-graph-trainer.2590949.1 ADDED Viewed

	@@ -0,0 +1,3 @@

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