Instructions to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct with Transformers:

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

pipe = pipeline("text-generation", model="drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct")
model = AutoModelForCausalLM.from_pretrained("drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct", 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

llama.cpp

How to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16
# Run inference directly in the terminal:
llama cli -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16
# Run inference directly in the terminal:
llama cli -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16
# Run inference directly in the terminal:
./llama-cli -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

Use Docker

docker model run hf.co/drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

LM Studio
Jan

vLLM

How to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

SGLang

How to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct 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 "drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct" \
    --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": "drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct",
		"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 "drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct" \
        --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": "drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct with Ollama:
```
ollama run hf.co/drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16
```
Unsloth Desktop

How to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

Configure the model in Pi

# Install Pi:
npm install -g @earendil-works/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Docker Model Runner
How to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct with Docker Model Runner:
```
docker model run hf.co/drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16
```

Lemonade

How to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

Run and chat with the model

lemonade run user.Open-GVP-Qwen2.5-14B-Instruct-BF16

List all available models

lemonade list

Hermes Agent

How to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct with OpenClaw:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16

Configure OpenClaw

# Install OpenClaw:
npm install -g openclaw@latest
# Register the local server and set it as the default model:
openclaw onboard --non-interactive --mode local \
  --auth-choice custom-api-key \
  --custom-base-url http://127.0.0.1:8080/v1 \
  --custom-model-id "drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16" \
  --custom-provider-id llama-cpp \
  --custom-compatibility openai \
  --custom-text-input \
  --accept-risk \
  --skip-health

Run OpenClaw

openclaw agent --local --agent main --message "Hello from Hugging Face"

drvivekpoojary commited on Aug 5

Commit

6db21a8

verified ·

1 Parent(s): e9aecb8

Upload 14 files

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Files changed (15) hide show

.gitattributes +1 -0
Modelfile +16 -0
README.md +215 -0
chat_template.jinja +54 -0
config.json +81 -0
generation_config.json +14 -0
model-00001-of-00006.safetensors +3 -0
model-00002-of-00006.safetensors +3 -0
model-00003-of-00006.safetensors +3 -0
model-00004-of-00006.safetensors +3 -0
model-00005-of-00006.safetensors +3 -0
model-00006-of-00006.safetensors +3 -0
model.safetensors.index.json +587 -0
tokenizer.json +3 -0
tokenizer_config.json +31 -0

.gitattributes CHANGED Viewed

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text

 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

Modelfile ADDED Viewed

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

+# ollama modelfile auto-generated by llamafactory
+FROM .
+TEMPLATE """{{ if .System }}<|im_start|>system
+{{ .System }}<|im_end|>
+{{ end }}{{ range .Messages }}{{ if eq .Role "user" }}<|im_start|>user
+{{ .Content }}<|im_end|>
+<|im_start|>assistant
+{{ else if eq .Role "assistant" }}{{ .Content }}<|im_end|>
+{{ end }}{{ end }}"""
+SYSTEM """You are Qwen, created by Alibaba Cloud. You are a helpful assistant."""
+PARAMETER stop "<|im_end|>"
+PARAMETER num_ctx 4096

README.md CHANGED Viewed

@@ -1,3 +1,218 @@
 ---
 license: apache-2.0
 ---

 ---
 license: apache-2.0
+language:
+- en
+base_model: Qwen/Qwen2.5-14B-Instruct
+tags:
+- pharmacovigilance
+- gvp
+- regulatory
+- qwen2.5
+- medical
+- drug-safety
+- instruction-tuning
+- gguf
+- safetensors
+- llama.cpp
+- ollama
+pipeline_tag: text-generation
+library_name: transformers
 ---
+# 💊 Open-GVP-Qwen2.5-14B-Instruct
+> Domain-adapted **Qwen2.5-14B** model specialized in **Good Pharmacovigilance Practices (GVP)** guidelines issued by the European Medicines Agency (EMA).
+This repository contains both the **merged Safetensors** version and **GGUF quantized** versions of the model.
+**Available formats:**
+- Merged Safetensors (for Transformers / vLLM / etc.)
+- GGUF: `BF16`, `Q8_0`, `Q6_K`
+---
+## 📖 Model Description
+**Open-GVP-Qwen2.5-14B-Instruct** is a domain-specialized version of [Qwen/Qwen2.5-14B-Instruct](https://huggingface.co/Qwen/Qwen2.5-14B-Instruct), fine-tuned using **LoRA** on a curated dataset of approximately **15,000 high-quality question-answer pairs** derived from the official EMA Good Pharmacovigilance Practices (GVP) guidelines.
+The model covers **all GVP Modules and related Addendums**, with particular strength in areas such as:
+- ICSR collection, management, and submission (Module VI)
+- Signal management (Module IX)
+- Risk management systems (Module V)
+- Periodic safety update reports (PSUR / PBRER)
+- Pharmacovigilance system master file (PSMF)
+> **Important**: This model performs best when used as part of a **RAG (Retrieval-Augmented Generation)** pipeline alongside the original GVP PDF documents, rather than as a standalone source of regulatory advice.
+---
+## 🗂️ Coverage
+| Category | Details |
+| :--- | :--- |
+| **GVP Modules** | All Modules |
+| **Addendum** | Included |
+| **Training Data Size** | ~15,000 instruction-format Q&A pairs |
+| **Primary Focus** | Regulatory interpretation & PV operations |
+---
+## 📦 Available Formats
+| Format | Files | Best For |
+| :--- | :--- | :--- |
+| **Merged Safetensors** | `model-00001-of-00004.safetensors` (4 shards) + config | Transformers, vLLM, TGI, full-precision inference |
+| **GGUF BF16** | `Open-GVP-Qwen2.5-14B-BF16.gguf` | Highest quality GGUF |
+| **GGUF Q8_0** | `Open-GVP-Qwen2.5-14B-Q8_0.gguf` | Excellent quality / speed balance |
+| **GGUF Q6_K** | `Open-GVP-Qwen2.5-14B-Q6_K.gguf` | Good quality with lower resource usage |
+**Recommendation**:
+- Use **Safetensors** for maximum quality and flexibility.
+- Use **Q8_0** or **Q6_K** GGUF for local / CPU-friendly deployment.
+---
+## 🚀 Quick Start
+### 1. Transformers (Safetensors)
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+model_name = "drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.bfloat16,
+    device_map="auto"
+)
+messages = [
+    {"role": "system", "content": "You are an expert pharmacovigilance assistant specialized in EMA Good Pharmacovigilance Practices (GVP)."},
+    {"role": "user", "content": "What is the definition of a serious adverse reaction according to GVP Module VI?"}
+]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer([text], return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.2)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+### 2. Ollama (GGUF)
+```bash
+# Recommended (Q8_0)
+ollama run hf.co/drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:Q8_0
+# Alternative options
+ollama run hf.co/drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:Q6_K
+ollama run hf.co/drvivekpoojary/Open-GVP-Qwen2.5-14B-Instruct:BF16
+```
+### 3. llama.cpp
+```bash
+./llama-cli \
+  -m Open-GVP-Qwen2.5-14B-Q8_0.gguf \
+  -p "What is the definition of a serious adverse reaction according to GVP Module VI?" \
+  -n 512 \
+  -c 4096 \
+  --temp 0.2
+```
+### 4. Python (llama-cpp-python)
+```python
+from llama_cpp import Llama
+llm = Llama(
+    model_path="Open-GVP-Qwen2.5-14B-Q8_0.gguf",
+    n_ctx=4096,
+    n_gpu_layers=-1,      # set to 0 for pure CPU
+    verbose=False
+)
+response = llm.create_chat_completion(
+    messages=[
+        {
+            "role": "system",
+            "content": "You are an expert pharmacovigilance assistant specialized in EMA Good Pharmacovigilance Practices (GVP)."
+        },
+        {
+            "role": "user",
+            "content": "What is the definition of a serious adverse reaction according to GVP Module VI?"
+        }
+    ],
+    max_tokens=512,
+    temperature=0.2
+)
+print(response["choices"][0]["message"]["content"])
+```
+---
+## ✅ Recommended Use Cases
+| Use Case | Description |
+| :--- | :--- |
+| **GVP Knowledge Assistant** | Answer questions on GVP modules, definitions, and requirements |
+| **PV Staff Training & Onboarding** | Support training of new pharmacovigilance team members |
+| **RAG Pipeline** | Use as the generator together with official GVP PDFs |
+| **Internal Regulatory Chatbot** | Backend for company-internal PV compliance assistants |
+| **Offline / Air-gapped Environments** | Run completely locally without internet access |
+| **Edge & Low-Resource Deployment** | Suitable for laptops and workstations (especially GGUF versions) |
+### ❌ Not Recommended For
+- Standalone regulatory decision-making
+- High-stakes compliance or submission decisions without human review
+- Replacing qualified pharmacovigilance professionals
+- Use outside the scope of EMA GVP guidelines
+- Generating content for regulatory submissions without expert verification
+---
+## 🔧 Training Details
+| Property | Value |
+| :--- | :--- |
+| **Base Model** | Qwen/Qwen2.5-14B-Instruct |
+| **Fine-tuning Method** | QLoRA |
+| **LoRA Rank** | 32 |
+| **LoRA Alpha** | 64 |
+| **LoRA Dropout** | 0.05 |
+| **Training Data** | ~15,000 GVP Q&A pairs (all modules) |
+| **Epochs** | 4 |
+| **Context Length** | 768 |
+| **Precision** | bfloat16 |
+| **Framework** | LlamaFactory |
+| **Hardware** | NVIDIA GPU (16 GB VRAM) |
+---
+## ⚠️ Disclaimer
+- This model is intended for **research, educational, and internal professional support purposes only**.
+- It does **not** constitute regulatory advice. All outputs should be carefully reviewed by qualified pharmacovigilance professionals before being used in any compliance, case processing, reporting, or decision-making context.
+- The model may produce incomplete, outdated, or inaccurate responses, particularly on complex or nuanced regulatory questions. The author assumes no liability for any decisions made based on the model’s outputs.
+- **No In-Training Evaluation:** Evaluation loss (`eval_loss`) was not computed during training, and per-epoch checkpoints were not preserved.
+---
+## 👤 Author
+**Dr. Vivek Poojary**
+Senior Pharmacovigilance Physician & Qualified Person for Pharmacovigilance (QPPV)
+---
+## 📄 License
+Apache License 2.0

chat_template.jinja ADDED Viewed

	@@ -0,0 +1,54 @@

+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json ADDED Viewed

	@@ -0,0 +1,81 @@

+{
+  "architectures": [
+    "Qwen2ForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 13824,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "max_window_layers": 70,
+  "model_type": "qwen2",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 8,
+  "pad_token_id": null,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 1000000.0,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "transformers_version": "5.8.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 152064
+}

generation_config.json ADDED Viewed

	@@ -0,0 +1,14 @@

+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
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