Instructions to use solvrays/solvrays-finetuned-pdf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use solvrays/solvrays-finetuned-pdf with Transformers:

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

pipe = pipeline("text-generation", model="solvrays/solvrays-finetuned-pdf")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("solvrays/solvrays-finetuned-pdf")
model = AutoModelForCausalLM.from_pretrained("solvrays/solvrays-finetuned-pdf")
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]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use solvrays/solvrays-finetuned-pdf with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/solvrays/solvrays-finetuned-pdf

SGLang

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

Docker Model Runner
How to use solvrays/solvrays-finetuned-pdf with Docker Model Runner:
```
docker model run hf.co/solvrays/solvrays-finetuned-pdf
```

singtan commited on 27 days ago

Commit

c013a11

verified ·

1 Parent(s): 60b70a5

Upload GemmaForCausalLM

Browse files

Files changed (3) hide show

README.md +6 -6
config.json +1 -1
model.safetensors +2 -2

README.md CHANGED Viewed

@@ -3,13 +3,13 @@ license: apache-2.0
 library_name: transformers
 base_model: google/gemma-2b
 tags:
-  - text-generation
-  - fine-tuned
-  - pdf-grounded
-  - zero-hallucination
-  - technical-provenance
 language:
-  - en
 pipeline_tag: text-generation
 ---

 library_name: transformers
 base_model: google/gemma-2b
 tags:
+- text-generation
+- fine-tuned
+- pdf-grounded
+- zero-hallucination
+- technical-provenance
 language:
+- en
 pipeline_tag: text-generation
 ---

config.json CHANGED Viewed

@@ -5,7 +5,7 @@
   "attention_bias": false,
   "attention_dropout": 0.0,
   "bos_token_id": 2,
-  "dtype": "float16",
   "eos_token_id": 1,
   "head_dim": 256,
   "hidden_act": "gelu",

   "attention_bias": false,
   "attention_dropout": 0.0,
   "bos_token_id": 2,
+  "dtype": "bfloat16",
   "eos_token_id": 1,
   "head_dim": 256,
   "hidden_act": "gelu",

model.safetensors CHANGED Viewed

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