Instructions to use avankumar/ChatChemE_V0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use avankumar/ChatChemE_V0 with Transformers:

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

pipe = pipeline("text-generation", model="avankumar/ChatChemE_V0", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("avankumar/ChatChemE_V0", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("avankumar/ChatChemE_V0", trust_remote_code=True)
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

vLLM

How to use avankumar/ChatChemE_V0 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "avankumar/ChatChemE_V0"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "avankumar/ChatChemE_V0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/avankumar/ChatChemE_V0

SGLang

How to use avankumar/ChatChemE_V0 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 "avankumar/ChatChemE_V0" \
    --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": "avankumar/ChatChemE_V0",
		"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 "avankumar/ChatChemE_V0" \
        --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": "avankumar/ChatChemE_V0",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use avankumar/ChatChemE_V0 with Docker Model Runner:
```
docker model run hf.co/avankumar/ChatChemE_V0
```

avankumar commited on Jul 16, 2025

Commit

0446b1d

verified ·

1 Parent(s): 909c55f

Update config.json

Browse files

Files changed (1) hide show

config.json +3 -7

config.json CHANGED Viewed

@@ -1,13 +1,9 @@
 {
   "architectures": [
-    "Phi3ForCausalLM"
   ],
   "attention_bias": false,
   "attention_dropout": 0.0,
-  "auto_map": {
-    "AutoConfig": "configuration_phi3.Phi3Config",
-    "AutoModelForCausalLM": "modeling_phi3.Phi3ForCausalLM"
-  },
   "bos_token_id": 1,
   "embd_pdrop": 0.0,
   "eos_token_id": 32000,
@@ -16,7 +12,7 @@
   "initializer_range": 0.02,
   "intermediate_size": 8192,
   "max_position_embeddings": 4096,
-  "model_type": "phi3",
   "num_attention_heads": 32,
   "num_hidden_layers": 32,
   "num_key_value_heads": 32,
@@ -33,4 +29,4 @@
   "transformers_version": "4.53.2",
   "use_cache": true,
   "vocab_size": 32064
-}

 {
   "architectures": [
+    "AutoModelForCausalLM"
   ],
   "attention_bias": false,
   "attention_dropout": 0.0,
   "bos_token_id": 1,
   "embd_pdrop": 0.0,
   "eos_token_id": 32000,
   "initializer_range": 0.02,
   "intermediate_size": 8192,
   "max_position_embeddings": 4096,
+  "model_type": "phi",  // changed from "phi3" to "phi" for compatibility
   "num_attention_heads": 32,
   "num_hidden_layers": 32,
   "num_key_value_heads": 32,
   "transformers_version": "4.53.2",
   "use_cache": true,
   "vocab_size": 32064
+}