Instructions to use trl-internal-testing/tiny-GPTNeoXForCausalLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use trl-internal-testing/tiny-GPTNeoXForCausalLM with Transformers:

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

pipe = pipeline("text-generation", model="trl-internal-testing/tiny-GPTNeoXForCausalLM")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("trl-internal-testing/tiny-GPTNeoXForCausalLM")
model = AutoModelForCausalLM.from_pretrained("trl-internal-testing/tiny-GPTNeoXForCausalLM", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use trl-internal-testing/tiny-GPTNeoXForCausalLM with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "trl-internal-testing/tiny-GPTNeoXForCausalLM"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "trl-internal-testing/tiny-GPTNeoXForCausalLM",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/trl-internal-testing/tiny-GPTNeoXForCausalLM

SGLang

How to use trl-internal-testing/tiny-GPTNeoXForCausalLM 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 "trl-internal-testing/tiny-GPTNeoXForCausalLM" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "trl-internal-testing/tiny-GPTNeoXForCausalLM",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "trl-internal-testing/tiny-GPTNeoXForCausalLM" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "trl-internal-testing/tiny-GPTNeoXForCausalLM",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use trl-internal-testing/tiny-GPTNeoXForCausalLM with Docker Model Runner:
```
docker model run hf.co/trl-internal-testing/tiny-GPTNeoXForCausalLM
```

Upload GPTNeoXForCausalLM

by albertvillanova HF Staff - opened 22 days ago

base: refs/heads/main

←

from: refs/pr/1

Discussion Files changed

-6

Files changed (3) hide show

config.json +3 -3
generation_config.json +1 -1
model.safetensors +2 -2

config.json CHANGED Viewed

@@ -7,7 +7,7 @@
   "bos_token_id": 0,
   "classifier_dropout": 0.1,
   "dtype": "float16",
-  "eos_token_id": 2,
   "hidden_act": "gelu",
   "hidden_dropout": 0.0,
   "hidden_size": 8,
@@ -25,8 +25,8 @@
   "rotary_emb_base": 10000,
   "rotary_pct": 0.25,
   "tie_word_embeddings": false,
-  "transformers_version": "4.57.3",
   "use_cache": true,
   "use_parallel_residual": true,
-  "vocab_size": 50277
 }

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   "classifier_dropout": 0.1,
   "dtype": "float16",
+  "eos_token_id": 0,
   "hidden_act": "gelu",
   "hidden_dropout": 0.0,
   "hidden_size": 8,
   "rotary_emb_base": 10000,
   "rotary_pct": 0.25,
   "tie_word_embeddings": false,
+  "transformers_version": "4.56.2",
   "use_cache": true,
   "use_parallel_residual": true,
+  "vocab_size": 50304
 }

generation_config.json CHANGED Viewed

@@ -2,5 +2,5 @@
   "_from_model_config": true,
   "bos_token_id": 0,
   "eos_token_id": 0,
-  "transformers_version": "4.57.3"
 }

   "_from_model_config": true,
   "bos_token_id": 0,
   "eos_token_id": 0,
+  "transformers_version": "4.56.2"
 }

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