Update README.md

README.md

@@ -6,11 +6,121 @@ tags:
 - text-generation-inference
 - transformers
 - llama3
+- llama
 - trl
 base_model: unsloth/llama-3-8b-Instruct
 ---
 
 # Uploaded  model
 
-- **Developed by:** Zardos
+- **Finetuned by:** Zardos
 - **License:** apache-2.0
+
+
+## How to use
+
+This repository contains two versions of Meta-Llama-3-8B-Instruct, for use with transformers and with the original `llama3` codebase.
+
+### Use with transformers
+
+You can run conversational inference using the Transformers pipeline abstraction, or by leveraging the Auto classes with the `generate()` function. Let's see examples of both.
+
+#### Transformers pipeline
+
+```python
+import transformers
+import torch
+
+model_id = "meta-llama/Meta-Llama-3-8B-Instruct"
+
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model_id,
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device_map="auto",
+)
+
+messages = [
+    {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
+    {"role": "user", "content": "Who are you?"},
+]
+
+prompt = pipeline.tokenizer.apply_chat_template(
+		messages, 
+		tokenize=False, 
+		add_generation_prompt=True
+)
+
+terminators = [
+    pipeline.tokenizer.eos_token_id,
+    pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = pipeline(
+    prompt,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+)
+print(outputs[0]["generated_text"][len(prompt):])
+```
+
+#### Transformers AutoModelForCausalLM
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "meta-llama/Meta-Llama-3-8B-Instruct"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+messages = [
+    {"role": "system", "content": "You are a pirate chatbot who always responds in pirate speak!"},
+    {"role": "user", "content": "Who are you?"},
+]
+
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(model.device)
+
+terminators = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = model.generate(
+    input_ids,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+)
+response = outputs[0][input_ids.shape[-1]:]
+print(tokenizer.decode(response, skip_special_tokens=True))
+```
+
+
+### Use with `llama3`
+
+Please, follow the instructions in the [repository](https://github.com/meta-llama/llama3)
+
+To download Original checkpoints, see the example command below leveraging `huggingface-cli`:
+
+```
+huggingface-cli download meta-llama/Meta-Llama-3-8B-Instruct --include "original/*" --local-dir Meta-Llama-3-8B-Instruct
+```
+
+For Hugging Face support, we recommend using transformers or TGI, but a similar command works.
+
+## Hardware and Software